Citation Intelligence

NPM · @AUTOMATELAB/CITATION-INTELLIGENCE

Check what Perplexity, Claude, ChatGPT, Gemini, and Google AI Overviews cite for any query.

Available components

npm · @automatelab/citation-intelligence 81

0 this week 81 81 Trust /100

Last scanned 5 Nov 2026 (10 hours ago)

Scores higher than 69% of npm servers

Category Marketing and SEO

Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security81

No malware found by supply-chain analysis.Pass
CVE check failed: a known high-severity CVE affects @modelcontextprotocol/sdk 1.29.0, a direct dependency. A fixed version is available. View diagnostics → Fail
No install/post-install scripts declared.Pass
42 of 138 dependencies flagged as unhealthy (2 deprecated). View diagnostics → Partial

Provenance & Transparency48

Source repository is publicly reachable at the declared URL. View diagnostics → Pass
Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
Clear OSI-approved license (MIT).Pass
Actively maintained (last published 22 days ago).Pass
Publishes a security disclosure policy (SECURITY.md).Pass

Schema Quality & AI Usability83

100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
AI-judged instruction clarity (excellent).Pass
Context-footprint check failed: tool/resource definitions use about 4378 tokens (~145/item across 30 items; 26 tools + 4 resources), over budget; trim descriptions and params. See how to fix → Fail
Usage-examples check failed: none of the tools include examples. See how to fix → Fail

Stability & Change Management100

No destabilizing schema changes in the last 30 days.Pass

Tool Coverage100

100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
100% of tool parameters carry a description.Pass
Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass

Tool Safety100

No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
We read all 26 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
An AI judge read all 27 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass

Capabilities100

Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

5 Nov 26 0
- CVE-2026-9678 affects this package: high ▼ security
- CVE-2026-16729 affects this package: high ▼ security
- CVE-2026-18149 affects this package: high ▼ security
- CVE-2026-109932 affects this package: high ▼ security
- CVE-2026-85008 affects this package: high ▼ security
- CVE-2026-111771 affects this package: high ▼ security
- CVE-2026-15157 affects this package: high ▼ security
- CVE-2026-84933 affects this package: high ▼ security
- GHSA-f897-62hf-6gxq affects this package: high ▼ security
- CVE-2026-84890 affects this package: high ▼ security
- CVE-2026-84947 affects this package: high ▼ security
- CVE-2026-84961 affects this package: high ▼ security
- CVE-2026-19534 affects this package: high ▼ security
- CVE-2026-109869 affects this package: high ▼ security
- CVE-2026-13697 affects this package: high ▼ security
- CVE-2026-14643 affects this package: high ▼ security
- CVE-2026-109829 affects this package: high ▼ security
- CVE-2026-109841 affects this package: high ▼ security
- CVE-2026-111768 affects this package: high ▼ security
- CVE-2026-6734 affects this package: high ▼ security
- CVE-2026-18540 affects this package: high ▼ security
- CVE-2026-41907 affects this package: high ▼ security
- CVE-2026-111769 affects this package: high ▼ security
- CVE-2026-109924 affects this package: high ▼ security
- CVE-2026-11525 affects this package: high ▼ security
- CVE-2026-87018 affects this package: high ▼ security
- CVE-2026-9679 affects this package: high ▼ security
- CVE-2023-54404 affects this package: high ▼ security
- CVE-2026-109383 affects this package: high ▼ security
- CVE-2026-85014 affects this package: high ▼ security
- CVE-2026-6733 affects this package: high ▼ security
- CVE-2026-104850 affects this package: high ▼ security
- CVE-2026-111767 affects this package: high ▼ security
- CVE-2026-16728 affects this package: high ▼ security
- CVE-2026-12151 affects this package: high ▼ security
- CVE-2026-87029 affects this package: high ▼ security
- CVE-2026-118663 affects this package: high ▼ security
- CVE-2026-9697 affects this package: high ▼ security
4 Nov 26 0
- CVE-2026-9678 affects this package: high ▼ security
- CVE-2026-16729 affects this package: high ▼ security
- CVE-2026-18149 affects this package: high ▼ security
- CVE-2026-109932 affects this package: high ▼ security
- CVE-2026-85008 affects this package: high ▼ security
- CVE-2026-111771 affects this package: high ▼ security
- CVE-2026-15157 affects this package: high ▼ security
- CVE-2026-84933 affects this package: high ▼ security
- GHSA-f897-62hf-6gxq affects this package: high ▼ security
- CVE-2026-84890 affects this package: high ▼ security
- CVE-2026-84947 affects this package: high ▼ security
- CVE-2026-84961 affects this package: high ▼ security
- CVE-2026-19534 affects this package: high ▼ security
- CVE-2026-109869 affects this package: high ▼ security
- CVE-2026-13697 affects this package: high ▼ security
- CVE-2026-14643 affects this package: high ▼ security
- CVE-2026-109829 affects this package: high ▼ security
- CVE-2026-109841 affects this package: high ▼ security
- CVE-2026-111768 affects this package: high ▼ security
- CVE-2026-6734 affects this package: high ▼ security
- CVE-2026-18540 affects this package: high ▼ security
- CVE-2026-41907 affects this package: high ▼ security
- CVE-2026-111769 affects this package: high ▼ security
- CVE-2026-109924 affects this package: high ▼ security
- CVE-2026-11525 affects this package: high ▼ security
- CVE-2026-87018 affects this package: high ▼ security
- CVE-2026-9679 affects this package: high ▼ security
- CVE-2023-54404 affects this package: high ▼ security
- CVE-2026-109383 affects this package: high ▼ security
- CVE-2026-85014 affects this package: high ▼ security
- CVE-2026-6733 affects this package: high ▼ security
- CVE-2026-104850 affects this package: high ▼ security
- CVE-2026-111767 affects this package: high ▼ security
- CVE-2026-16728 affects this package: high ▼ security
- CVE-2026-12151 affects this package: high ▼ security
- CVE-2026-87029 affects this package: high ▼ security
- CVE-2026-118663 affects this package: high ▼ security
- CVE-2026-9697 affects this package: high ▼ security
3 Nov 26 +1
- CVE-2026-9678 affects this package: high ▼ security
- CVE-2026-16729 affects this package: high ▼ security
- CVE-2026-18149 affects this package: high ▼ security
- CVE-2026-109932 affects this package: high ▼ security
- CVE-2026-85008 affects this package: high ▼ security
- CVE-2026-111771 affects this package: high ▼ security
- CVE-2026-15157 affects this package: high ▼ security
- CVE-2026-84933 affects this package: high ▼ security
- GHSA-f897-62hf-6gxq affects this package: high ▼ security
- CVE-2026-84890 affects this package: high ▼ security
- CVE-2026-84947 affects this package: high ▼ security
- CVE-2026-84961 affects this package: high ▼ security
- CVE-2026-19534 affects this package: high ▼ security
- CVE-2026-109869 affects this package: high ▼ security
- CVE-2026-13697 affects this package: high ▼ security
- CVE-2026-14643 affects this package: high ▼ security
- CVE-2026-109829 affects this package: high ▼ security
- CVE-2026-109841 affects this package: high ▼ security
- CVE-2026-111768 affects this package: high ▼ security
- CVE-2026-6734 affects this package: high ▼ security
- CVE-2026-18540 affects this package: high ▼ security
- CVE-2026-41907 affects this package: high ▼ security
- CVE-2026-111769 affects this package: high ▼ security
- CVE-2026-109924 affects this package: high ▼ security
- CVE-2026-11525 affects this package: high ▼ security
- CVE-2026-87018 affects this package: high ▼ security
- CVE-2026-9679 affects this package: high ▼ security
- CVE-2023-54404 affects this package: high ▼ security
- CVE-2026-109383 affects this package: high ▼ security
- CVE-2026-85014 affects this package: high ▼ security
- CVE-2026-6733 affects this package: high ▼ security
- CVE-2026-104850 affects this package: high ▼ security
- CVE-2026-111767 affects this package: high ▼ security
- CVE-2026-16728 affects this package: high ▼ security
- CVE-2026-12151 affects this package: high ▼ security
- CVE-2026-87029 affects this package: high ▼ security
- CVE-2026-118663 affects this package: high ▼ security
- CVE-2026-9697 affects this package: high ▼ security
- Stability: 0.97 → pass security
2 Nov 26 −1
- CVE-2026-9678 affects this package: high ▼ security
- CVE-2026-16729 affects this package: high ▼ security
- CVE-2026-18149 affects this package: high ▼ security
- CVE-2026-109932 affects this package: high ▼ security
- CVE-2026-85008 affects this package: high ▼ security
- CVE-2026-111771 affects this package: high ▼ security
- CVE-2026-15157 affects this package: high ▼ security
- CVE-2026-84933 affects this package: high ▼ security
- GHSA-f897-62hf-6gxq affects this package: high ▼ security
- CVE-2026-84890 affects this package: high ▼ security
- CVE-2026-84947 affects this package: high ▼ security
- CVE-2026-84961 affects this package: high ▼ security
- CVE-2026-19534 affects this package: high ▼ security
- CVE-2026-109869 affects this package: high ▼ security
- CVE-2026-13697 affects this package: high ▼ security
- CVE-2026-14643 affects this package: high ▼ security
- CVE-2026-109829 affects this package: high ▼ security
- CVE-2026-109841 affects this package: high ▼ security
- CVE-2026-111768 affects this package: high ▼ security
- CVE-2026-6734 affects this package: high ▼ security
- CVE-2026-18540 affects this package: high ▼ security
- CVE-2026-41907 affects this package: high ▼ security
- CVE-2026-111769 affects this package: high ▼ security
- CVE-2026-109924 affects this package: high ▼ security
- CVE-2026-11525 affects this package: high ▼ security
- CVE-2026-87018 affects this package: high ▼ security
- CVE-2026-9679 affects this package: high ▼ security
- CVE-2023-54404 affects this package: high ▼ security
- CVE-2026-109383 affects this package: high ▼ security
- CVE-2026-85014 affects this package: high ▼ security
- CVE-2026-6733 affects this package: high ▼ security
- CVE-2026-104850 affects this package: high ▼ security
- CVE-2026-111767 affects this package: high ▼ security
- CVE-2026-16728 affects this package: high ▼ security
- CVE-2026-12151 affects this package: high ▼ security
- CVE-2026-87029 affects this package: high ▼ security
- CVE-2026-118663 affects this package: high ▼ security
- CVE-2026-9697 affects this package: high ▼ security
- Stability: pass → 0.97 functional
1 Nov 26 0
- CVE-2026-9678 affects this package: high ▼ security
- CVE-2026-16729 affects this package: high ▼ security
- CVE-2026-18149 affects this package: high ▼ security
- CVE-2026-109932 affects this package: high ▼ security
- CVE-2026-85008 affects this package: high ▼ security
- CVE-2026-111771 affects this package: high ▼ security
- CVE-2026-15157 affects this package: high ▼ security
- CVE-2026-84933 affects this package: high ▼ security
- GHSA-f897-62hf-6gxq affects this package: high ▼ security
- CVE-2026-84890 affects this package: high ▼ security
- CVE-2026-84947 affects this package: high ▼ security
- CVE-2026-84961 affects this package: high ▼ security
- CVE-2026-19534 affects this package: high ▼ security
- CVE-2026-109869 affects this package: high ▼ security
- CVE-2026-13697 affects this package: high ▼ security
- CVE-2026-14643 affects this package: high ▼ security
- CVE-2026-109829 affects this package: high ▼ security
- CVE-2026-109841 affects this package: high ▼ security
- CVE-2026-111768 affects this package: high ▼ security
- CVE-2026-6734 affects this package: high ▼ security
- CVE-2026-18540 affects this package: high ▼ security
- CVE-2026-41907 affects this package: high ▼ security
- CVE-2026-111769 affects this package: high ▼ security
- CVE-2026-109924 affects this package: high ▼ security
- CVE-2026-11525 affects this package: high ▼ security
- CVE-2026-87018 affects this package: high ▼ security
- CVE-2026-9679 affects this package: high ▼ security
- CVE-2023-54404 affects this package: high ▼ security
- CVE-2026-109383 affects this package: high ▼ security
- CVE-2026-85014 affects this package: high ▼ security
- CVE-2026-6733 affects this package: high ▼ security
- CVE-2026-104850 affects this package: high ▼ security
- CVE-2026-111767 affects this package: high ▼ security
- CVE-2026-16728 affects this package: high ▼ security
- CVE-2026-12151 affects this package: high ▼ security
- CVE-2026-87029 affects this package: high ▼ security
- CVE-2026-118663 affects this package: high ▼ security
- CVE-2026-9697 affects this package: high ▼ security
31 Oct 26 0

We did not load change detail this far back for this component, so this day may have recorded more than is shown.
- CVE-2026-9678 affects this package: high ▼ security
- CVE-2026-16729 affects this package: high ▼ security
- CVE-2026-18149 affects this package: high ▼ security
- CVE-2026-109932 affects this package: high ▼ security
- CVE-2026-85008 affects this package: high ▼ security
- CVE-2026-111771 affects this package: high ▼ security
27 Oct 26 +1

We did not load change detail this far back for this component, so this day may have recorded more than is shown.
26 Oct 26 −1

We did not load change detail this far back for this component, so this day may have recorded more than is shown.

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Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 5 Nov 2026 · Analysed npm/@automatelab/citation-intelligence@0.12.1

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result	No attestation
Ecosystem	npm

Background: How many MCP packages publish verified provenance →

Vulnerabilities 38 findings

ID	CVE	Severity	Vector	Fix available
GHSA-rmxm-3fg6-px4f	CVE-2026-118663	medium	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N	yes
GHSA-22jm-h49p-29qw	CVE-2026-111767	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L	yes
GHSA-46jr-4wx8-v453	CVE-2026-111768	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-6prh-2h8m-c8cw	CVE-2026-111769	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:N	yes
GHSA-6qxp-vccf-f47h	CVE-2026-104850	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N	yes
GHSA-f897-62hf-6gxq		high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-rvq5-wwqv-78pq	CVE-2026-111771	medium	CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:N	yes
GHSA-2gqq-gqf2-x968	CVE-2026-84947	low	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:N	yes
GHSA-2jfj-6hjv-fm6j	CVE-2026-84933	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:N	yes
GHSA-2m5v-pch6-74hx	CVE-2026-109383	high	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N	yes
GHSA-35p6-xmwp-9g52	CVE-2026-6733	low	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:N	yes
GHSA-3xpg-4rpp-hhhm	CVE-2026-84890	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-4cwx-7wf7-3272	CVE-2026-13697	high	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:H	yes
GHSA-4qv8-2p9j-2685	CVE-2026-109924	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-4w7w-5xrc-9h26	CVE-2026-109829	high	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N	yes
GHSA-55wc-3pg8-jfw6	CVE-2026-87029	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-8436-99hf-9mmv	CVE-2026-85008	low	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:N	yes
GHSA-8xcm-r25x-g524	CVE-2026-16728	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N	yes
GHSA-9fm3-97px-rjf6	CVE-2026-109932	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-f72v-6w45-q472	CVE-2026-109841	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:H/A:N	yes
GHSA-g8m3-5g58-fq7m	CVE-2026-11525	low	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:N	yes
GHSA-hm92-r4w5-c3mj	CVE-2026-6734	high	CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H	yes
GHSA-jr45-8vmc-qm54	CVE-2026-14643	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N	yes
GHSA-m8rv-5g2x-5cg5	CVE-2026-15157	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:N	yes
GHSA-p88m-4jfj-68fv	CVE-2026-9679	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:H/A:N	yes
GHSA-pmjh-fq2x-6v4x	CVE-2026-18149	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-pr7r-676h-xcf6	CVE-2026-9678	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N	yes
GHSA-qrxm-fqhp-jwvm	CVE-2026-87018	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-r53p-7pc4-xj5r	CVE-2026-18540	low	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:N	yes
GHSA-rfgv-xxqx-mfg5	CVE-2026-19534	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-rx4f-c7p8-82vq	CVE-2026-85014	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-v3r7-h72x-cjcm	CVE-2026-16729	medium	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N	yes
GHSA-vmh5-mc38-953g	CVE-2026-9697	high	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N	yes
GHSA-vxpw-j846-p89q	CVE-2026-12151	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-w293-vg96-wgc3	CVE-2026-84961	high	CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N	yes
GHSA-xjj6-f33q-929c	CVE-2026-109869	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H	yes
GHSA-w5hq-g745-h8pq	CVE-2026-41907	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N	yes
GHSA-mrhx-c7xc-m3w5	CVE-2023-54404	high	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H	yes

Background: What a vulnerability scan can and cannot prove →

Dependencies 138 packages

Packages resolved	138
Deprecated	2
Stale	41
Tree resolution	Complete

Background: SBOMs and build attestations, explained →

MCP tools · 26 exposed · ~4,260 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens

audit_crawler_access ~180

Verify that major AI crawlers (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, CCBot, Google-Extended, Applebot-Extended, Bytespider, Meta-ExternalAgent, plus real-time fetch UAs) can fetch a URL. Parses robots.txt and does a live GET with each bot's User-Agent. Surfaces robots.txt blocks AND UA-based gating that breaks AI citation.

Input Output Examples

Name	Type	Req	Description
bots	array	–	Override the default bot list. Each entry is a User-Agent token (e.g. 'GPTBot', 'ClaudeBot').
fetch_with_ua	boolean	–	If true, do a live GET as each bot's User-Agent and report status. Disable to only parse robots.txt (no extra requests).
url	string	yes	Page URL to test for AI crawler access.

Name	Type	Req	Description
bots	array	yes	Per-bot access verdict combining robots.txt + live UA test.
fetched_at	string	yes	UTC ISO-8601 timestamp.
note	string	–	–
robots_error	string\|null	yes	Error message if robots.txt fetch failed.
robots_present	boolean	yes	Whether a non-empty robots.txt was found.
robots_status	number\|null	yes	HTTP status of the robots.txt fetch.
robots_url	string	yes	robots.txt URL that was parsed.
summary	object	yes	–
url	string	yes	The URL that was audited.

No examples provided.

audit_llms_txt ~208

Generate an llms.txt file (https://llmstxt.org spec) from a sitemap. Parses sitemap.xml + nested indexes, groups URLs by top-level path, and emits a Markdown document with H1+description+sectioned link lists. Set fetch_titles=true to pull <title> per URL (slower, richer output).

Input Output Examples

Name	Type	Req	Description
fetch_titles	boolean	–	If true, fetch each URL to extract <title> for richer links. Slower (one HEAD-ish GET per URL). Default false uses the URL path as the link text.
limit	integer	–	Max URLs to include. Truncated after sitemap parse, before title fetch.
site_description	string	–	One-paragraph site description placed under the H1. Optional but strongly recommended.
site_title	string	yes	Site title - top H1 in the generated llms.txt file.
sitemap_url	string	yes	URL of sitemap.xml (or sitemap index). Nested sitemaps are followed.

Name	Type	Req	Description
content	string	yes	Generated llms.txt file content; save to /llms.txt at site root.
fetched_at	string	yes	UTC ISO-8601 timestamp.
note	string	–	–
sections	number	yes	Number of top-level sections in the generated file.
sitemap_url	string	yes	Sitemap URL that was processed.
titles_fetched	number	yes	Number of pages fetched to extract <title>.
total_urls_in_sitemap	number	yes	Total URLs found in the sitemap.
urls_included	number	yes	URLs included after applying the limit.

No examples provided.

audit_schema ~113

Deep schema.org validation for a URL. Parses every JSON-LD block and microdata node, checks required fields per @type (Article needs headline+author+datePublished, FAQPage needs mainEntity, HowTo needs step, etc.), and flags missing fields and malformed JSON-LD. Returns issues list and a valid/invalid verdict. Use to fix structured-data bugs that predict_citation flags but can't explain.

Input Output Examples

Name	Type	Req	Description
url	string	yes	URL whose JSON-LD and microdata to validate against schema.org expected fields.

Name	Type	Req	Description
fetched_at	string	yes	UTC ISO-8601 timestamp.
issues	array	yes	Validation issues found.
json_ld_blocks	number	yes	Total JSON-LD blocks found.
json_ld_parse_errors	number	yes	Number of JSON-LD blocks that failed to parse.
microdata_types_present	array	yes	Schema types found via microdata (itemtype).
note	string	–	–
schema_types_present	array	yes	@type values found across all JSON-LD blocks.
summary	object	yes	–
url	string	yes	URL that was audited.

No examples provided.

audit_sitemap ~113

Fetch a sitemap.xml (or sitemap index) and run predict_citation on every URL. Returns results sorted worst-score-first. Surfaces systemic issues across a whole site in one pass. Zero engine keys needed.

Input Output Examples

Name	Type	Req	Description
concurrency	integer	–	Parallel predict_citation calls. Higher is faster but more rate-limit risk.
limit	integer	–	Max URLs to score. Sitemap is sliced after parsing.
sitemap_url	string	yes	URL of sitemap.xml (or a sitemap index). Nested sitemaps are followed.

Name	Type	Req	Description
audited	number	yes	Number of URLs that were scored.
average_score	number	yes	Mean predict_citation score across scored URLs.
errors	array	yes	URLs whose audit threw an error.
fetched_at	string	yes	UTC ISO-8601 timestamp.
sitemap_url	string	yes	The sitemap URL that was audited.
total_urls	number	yes	Total URLs found in the sitemap.
worst_first	array	yes	Up to 20 lowest-scoring URLs, worst first.

No examples provided.

audit_sitemap_map ~160

Cross-reference a sitemap with the citation cache. For each sitemap URL, reports whether it appears in cached citations (and how many queries/engines cited it). Inverse of audit_sitemap: not 'how citable is each URL', but 'has each URL actually been cited yet'. Cache must be primed via check_citations or run_panel first.

Input Output Examples

Name	Type	Req	Description
domain	string	–	Domain to look up citations for. If omitted, inferred from the sitemap host.
limit	integer	–	Max sitemap URLs to consider.
since	string	–	ISO date floor; only count citations recorded on or after this date.
sitemap_url	string	yes	URL of sitemap.xml (or a sitemap index). Nested sitemaps are followed.

Name	Type	Req	Description
citations_in_cache	number	yes	Total citation cache entries for this domain.
coverage_pct	number	yes	Percentage of sitemap URLs that have been cited (0-100).
domain	string	yes	Domain whose citation cache was queried.
fetched_at	string	yes	UTC ISO-8601 timestamp.
mapped	number	yes	URLs found in the citation cache.
mapped_urls	array	yes	Sitemap URLs present in the cache, sorted by citation count desc.
note	string	–	–
since	string	–	–
sitemap_url	string	yes	The sitemap that was processed.
total_urls	number	yes	Total sitemap URLs considered.
unmapped	number	yes	URLs not yet seen in the citation cache.
unmapped_urls	array	yes	Sitemap URLs not yet cited (up to 200).

No examples provided.

audit_structured_data ~133

Suggest missing JSON-LD additions for a URL. Fetches the page, detects existing schema types, and returns ready-to-paste templates for types that are missing but signalled by page content (BlogPosting from og:type=article or bylines, FAQPage from Q&A pairs, HowTo from numbered steps, BreadcrumbList from nested paths, Organization on homepages). Templates are pre-filled from page metadata where possible; fields marked FILL: require manual completion.

Input Output Examples

Name	Type	Req	Description
url	string	yes	URL to inspect for missing JSON-LD. The page is fetched and its content signals are used to suggest schema types.

Name	Type	Req	Description
fetched_at	string	yes	UTC ISO-8601 timestamp.
note	string	–	–
schema_types_present	array	yes	@type values already present on the page.
signals_detected	object	yes	Content signals detected (e.g. og:type=article).
suggestions	array	yes	Schema additions suggested for this page.
summary	object	yes	–
url	string	yes	URL that was inspected.

No examples provided.

citations_check ~247

Return URLs cited by an AI engine (Perplexity, Claude, ChatGPT, Gemini, or Bing) for a query. Use this when an agent or user wants to see what sources an AI search engine grounds answers on. Requires at least one engine API key; auto-picks the first available.

Input Output Examples

Name	Type	Req	Description
engine	string	–	Engine to query. • perplexity / google_ai_mode — consumer_scrape: closest to real product behavior. • claude / openai / gemini — api_proxy: API-tier call, may differ from consumer product. • bing_ser…
max_results	integer	–	Maximum citations to return.
perplexity_model	string	–	Perplexity model override (e.g. 'sonar', 'sonar-pro', 'sonar-reasoning'). Only used when engine='perplexity'. Defaults to 'sonar-pro'.
query	string	yes	The search query to test (what would a user ask an AI?)

Name	Type	Req	Description
cached	boolean	yes	Whether the result was served from the local cache.
citations	array	yes	Cited URLs ordered by rank.
engine	string	yes	Engine used for this response.
fetched_at	string	yes	UTC ISO-8601 timestamp of the fetch.
interpretation_note	string	yes	Guidance on how to interpret results from this engine.
query	string	yes	The query that was executed.
raw_answer	string\|null	–	Raw answer text from the engine, if available. Absent for web_rank engines (bing_serp, brave_serp) that return ranked URLs without a synthesized answer.
surface	string	yes	Engine surface type: consumer_scrape, api_proxy, or web_rank.

No examples provided.

citations_evidence ~183

Extract the cited snippet from the AI engine's raw answer for each citation. Calls check_citations, then for each returned URL finds the first mention in raw_answer and returns a context window plus the nearest quoted span or containing sentence. Use to see *why* an engine cited a URL, not just *that* it did. Returns 'not found' for engines without raw_answer (Bing, Brave).

Input Output Examples

Name	Type	Req	Description
context_chars	integer	–	Half-width of the snippet window around each citation mention (chars). Total snippet is up to 2x this.
engine	string	–	AI engine to query. web_rank engines (bing_serp, brave_serp) lack raw_answer and return no evidence.
max_results	integer	–	Max citations to extract evidence for.
query	string	yes	Search query whose AI answer to extract citation evidence from.

Name	Type	Req	Description
citations_total	number	yes	–
engine	string	yes	Engine used.
evidence	array	yes	Per-citation evidence extracted from the raw answer.
evidence_found	number	yes	Citations whose URL was located in the raw answer.
fetched_at	string	yes	UTC ISO-8601 timestamp.
has_raw_answer	boolean	yes	Whether the engine returned a raw answer.
note	string	–	–
query	string	yes	The query whose answer was analyzed.
raw_answer_chars	number	yes	Length of the engine's raw answer.

No examples provided.

citations_freshness ~129

Score how recent the pages cited for a query are. Calls check_citations, then collects dateModified for each cited URL, returns a 0-100 recency_score (halflife=365d) plus per-URL freshness bucket (fresh/current/stale/ancient/unknown). Surfaces queries where AI cites old content - opportunity to ship fresher.

Input Output Examples

Name	Type	Req	Description
engine	string	–	AI engine to query for the citation set.
max_results	integer	–	How many cited URLs to inspect.
query	string	yes	Search query whose cited URLs to score for freshness.

Name	Type	Req	Description
average_days_old	number\|null	yes	Mean age in days across URLs with a detectable dateModified.
buckets	object	yes	Freshness bucket distribution.
engine	string	yes	Engine used.
fetched_at	string	yes	UTC ISO-8601 timestamp.
note	string	–	–
per_url	array	yes	Per-URL freshness details.
query	string	yes	The query whose citations were scored.
recency_score	number	yes	0-100 average recency weight across cited URLs (halflife=365d).

No examples provided.

citations_predict ~85

Score citation likelihood for a URL from public signals (Wikipedia link presence, schema.org markup, /llms.txt, GitHub and Reddit references, canonical hygiene, HTTPS). No LLM fired - all heuristic. Returns 0-100 score, grade, signal breakdown, and ranked fixes.

Input Output Examples

Name	Type	Req	Description
url	string	yes	URL to score for citation likelihood. Must be absolute http(s).

Name	Type	Req	Description
fetched_at	string	yes	UTC ISO-8601 timestamp.
fixes	array	yes	Ranked list of concrete improvements to raise the score.
grade	string	yes	Letter grade (A-F) derived from the score.
score	number	yes	0-100 citation likelihood score.
signals	object	yes	Per-signal boolean/numeric values used to compute the score.
url	string	yes	URL that was scored.

No examples provided.

citations_provenance ~156

Fan a query out across multiple AI engines and report per-URL cross-engine consensus. Returns each unique cited URL with the list of engines that cited it, plus a consensus_urls list (URLs cited by ALL engines). High engine_count = strong cross-engine citation signal; engine_count=1 = engine-specific.

Input Output Examples

Name	Type	Req	Description
engines	array	–	Engines to query. If omitted, uses all LLM engines with a configured API key (perplexity, claude, openai, gemini, google_ai_mode). Include bing_serp/brave_serp only when you explicitly want web_rank…
max_results	integer	–	Max citations per engine.
query	string	yes	Search query to fan out across multiple engines.

Name	Type	Req	Description
consensus_urls	array	yes	URLs cited by ALL succeeding engines (requires >=2 engines).
engines	array	yes	Per-engine run summary.
engines_queried	number	yes	–
engines_succeeded	number	yes	–
fetched_at	string	yes	UTC ISO-8601 timestamp.
note	string	–	–
per_url	array	yes	All unique cited URLs sorted by cross-engine consensus (engine_count desc).
query	string	yes	The query that was fanned across engines.
summary	object	yes	–

No examples provided.

citations_trend ~167

Report citation rate over time for a panel from stored snapshots. Read-only; cache-only — makes no API calls to any AI engine and costs no API quota. Reads snapshot files from <config>/snapshots/<panel>/. Returns: snapshots[] (one entry per panel_run invocation, each with timestamp and citation_rate), plus per-query deltas (gained/lost/unchanged) comparing first vs last snapshot. Returns an empty series when no snapshots exist yet. No auth required. No rate limits. Use panel_run to accumulate snapshots first; use since to restrict the time window.

Input Output Examples

Name	Type	Req	Description
panel	string	yes	Panel name to report on.
since	string	–	ISO date floor, e.g. '2026-01-01'. Only include snapshots on or after.

Name	Type	Req	Description
domain	string	–	Domain tracked by the panel.
first_taken_at	string	–	Timestamp of the oldest snapshot.
last_taken_at	string	–	Timestamp of the newest snapshot.
panel	string	yes	Panel name.
query_deltas	array	yes	Per-query changes between first and last snapshot.
series	array	yes	Time-series of citation rates, one entry per snapshot.
snapshots	number	yes	Number of snapshots available.

No examples provided.

competitors_canonical_set ~184

Fan a query across engines and aggregate citations by registered domain (not URL). Returns top competitor domains ranked by cross-engine consensus, with per-engine breakdown and top URLs per domain. Use to identify the canonical competitor set for a query - the domains every engine treats as authoritative.

Input Output Examples

Name	Type	Req	Description
engines	array	–	Engines to query. If omitted, uses all LLM engines with a configured API key (google_ai_mode, perplexity, claude, openai, gemini). Include bing_serp/brave_serp only for web_rank comparison.
exclude_domains	array	–	Domains to filter out (e.g. your own brand, Wikipedia, Reddit). Suffix-match.
max_results	integer	–	Max citations per engine.
query	string	yes	Search query to fan out across engines.
top_n	integer	–	Max competitor domains to return.

Name	Type	Req	Description
domains	array	yes	Competitor domains ranked by cross-engine consensus.
engines	array	yes	Per-engine run summary.
engines_queried	number	yes	–
engines_succeeded	number	yes	–
excluded_domains	array	yes	Registered domains that were filtered out.
fetched_at	string	yes	UTC ISO-8601 timestamp.
note	string	–	–
query	string	yes	The query that was fanned across engines.
top_n	number	yes	Maximum domains returned.
total_unique_domains	number	yes	Total unique competitor domains found before top_n truncation.

No examples provided.

competitors_compare ~82

Run predict_citation on 2-10 URLs and return a side-by-side signal table plus a list of signals where the URLs diverge. Use to compare your URL to top-cited competitors for the same query.

Input Output Examples

Name	Type	Req	Description
urls	array	yes	URLs to compare side-by-side. 2-10 URLs. One is typically yours and the rest are cited competitors.

Name	Type	Req	Description
diverging_signals	array	yes	Signals where at least one URL differs from the others.
fetched_at	string	yes	UTC ISO-8601 timestamp.
rows	array	yes	Per-URL predict_citation rows (or { url, error } on failure).

No examples provided.

competitors_compete ~151

End-to-end competitive snapshot for a single query. Calls check_citations to get the cited URLs, then runs compare_domains on your_url vs the top cited competitors. Returns your score, the average competitor score, and the gap.

Input Output Examples

Name	Type	Req	Description
engine	string	–	AI engine to query for the citation set. 'auto' picks the first available key.
max_competitors	integer	–	How many cited URLs to compare against your_url. Capped at 9 (compare_domains accepts max 10 URLs total including yours).
query	string	yes	Search query to test (what would a user ask an AI?).
your_url	string	yes	Your URL to benchmark against the cited competitors.

Name	Type	Req	Description
average_competitor_score	number\|null	yes	Mean score across competitor URLs.
comparison	–	yes	Full compare_domains result.
competitors	array	yes	Competitor URLs that were compared.
engine	string	yes	Engine used for the citation fetch.
fetched_at	string	yes	UTC ISO-8601 timestamp.
query	string	yes	The query that was tested.
score_gap	number\|null	yes	your_score minus average_competitor_score.
your_in_citations	boolean	yes	Whether your URL appeared in the engine's citation list.
your_score	number\|null	yes	predict_citation score for your URL (null on error).
your_url	string	yes	Your URL that was benchmarked.

No examples provided.

domain_am_i_cited ~171

Check whether a domain is cited by an AI engine across a cluster of queries. Returns per-query presence, rank, and a citation-rate summary. Use to measure visibility for a brand, product, or content site in AI search.

Input Output Examples

Name	Type	Req	Description
domain	string	yes	Domain to check, e.g. 'automatelab.tech' (without protocol).
engine	string	–	LLM engine to check for citations. 'auto' runs all available LLM engines and returns per-engine breakdown + cross-engine consensus. Pin to a specific engine to reduce cost. 'bing_serp' and 'brave_ser…
queries	array	yes	Queries to test the domain against. 1-20 queries per call.

Name	Type	Req	Description
consensus	object	–	Cross-engine consensus stats (multi_engine mode).
domain	string	yes	The domain that was checked.
engine	string	–	Engine used (single_engine mode only).
engines	array	–	Per-engine summary rows (multi_engine mode).
fetched_at	string	yes	UTC ISO-8601 timestamp.
mode	string	yes	Whether one or multiple engines were queried.
per_engine	array	–	Full per-engine detail (multi_engine mode).
results	array	–	Per-query results (single_engine mode).
summary	object	–	Aggregate summary (single_engine mode).
surface	string	–	Engine surface type (single_engine mode only).

No examples provided.

domain_cited_for ~128

List queries that the given domain has been cited for, served from the local cache. Build up a corpus by calling check_citations or am_i_cited first; cited_for queries it without spending API budget.

Input Output Examples

Name	Type	Req	Description
domain	string	yes	Domain to look up, e.g. 'automatelab.tech'.
engine	string	–	Filter by engine. Omit to include all.
limit	integer	–	Maximum results.
since	string	–	ISO date floor, e.g. '2026-01-01'. Only return entries fetched on or after this date.

Name	Type	Req	Description
domain	string	yes	Domain that was looked up.
engine_filter	string	–	Engine filter applied, if any.
results	array	yes	Cache entries where this domain was cited.
since	string	–	ISO date floor applied, if any.
source	string	yes	Always 'local_cache' — no external calls made.
total	number	yes	Total entries returned.

No examples provided.

domain_cited_for_diff ~153

Diff cited_for between two time windows for a domain. Returns queries gained (cited now, not before baseline_until) and queries lost (cited before, not since current_since). Cache-only, no API spend. Use to track citation drift over time after publishing or migrating content.

Input Output Examples

Name	Type	Req	Description
baseline_until	string	yes	ISO date (or ISO datetime). Baseline window = all cache entries fetched on or before this timestamp.
current_since	string	–	ISO date floor for the 'current' window. Defaults to baseline_until.
domain	string	yes	Domain to diff, e.g. 'automatelab.tech'.
engine	string	–	Filter by engine. Omit to include all.

Name	Type	Req	Description
baseline_until	string	yes	Upper bound of the baseline window.
counts	object	yes	–
current_since	string	yes	Lower bound of the current window.
domain	string	yes	Domain that was diffed.
engine_filter	string	–	Engine filter applied, if any.
fetched_at	string	yes	UTC ISO-8601 timestamp.
gained	array	yes	Queries gained (newly cited) since the baseline.
lost	array	yes	Queries lost (were cited, no longer are).
source	string	yes	–
unchanged_queries	array	yes	Queries cited in both windows.

No examples provided.

panel_run ~175

Run a saved panel through am_i_cited and append a timestamped snapshot. Side effects: makes external API calls to the configured AI engine (costs API quota); writes one snapshot file to disk at <config>/snapshots/<panel>/<iso>.json. Requires at least one engine API key (same as am_i_cited). Returns per-query citation presence and a citation_rate summary for the run. Use panel_track to create a panel first; use citations_trend to read the accumulated trend after multiple runs.

Input Output Examples

Name	Type	Req	Description
domain	string	–	Override the panel's default domain for this run.
engine	string	–	AI engine to query. Use bing_serp/brave_serp for web_rank comparison only — am_i_cited will refuse them.
name	string	yes	Panel name previously saved via track_queries.

Name	Type	Req	Description
saved_to	string	yes	Absolute file path of the snapshot that was written.
snapshot	object	yes	The snapshot that was appended.

No examples provided.

panel_track ~174

Save, load, or list named query panels. A panel is a persisted set of queries you want to monitor over time (e.g. editorial-watchlist). Use action=save with queries[] to create, action=load to read, action=list to enumerate. Panels live under <config>/panels/<name>.json.

Input Output Examples

Name	Type	Req	Description
action	string	–	'save' writes the panel, 'load' returns an existing panel, 'list' enumerates all panels.
domain	string	–	Default domain to track for this panel, e.g. 'automatelab.tech'.
name	string	yes	Panel name, e.g. 'editorial-watchlist'. Used to save and recall the query set.
queries	array	–	Queries to save under this panel. Omit to read the existing panel.

Name	Type	Req	Description
error	string	–	Error message when the panel was not found.
panel	object	–	The panel object that was saved or loaded.
panels	array	–	All panel names (action=list).
saved	boolean	–	True when action=save succeeded.

No examples provided.

report_visibility ~332

Turnkey AI visibility report for a domain across a query set. Composes check_citations over every query (or a saved panel) and returns the metrics AI-visibility trackers sell as a dashboard, in one call: mention frequency (citation_rate), share_of_voice vs competitors, average rank when cited, and brand sentiment from the answer text. Side effects: one check_citations call per query (costs API quota for uncached queries; cached queries are free). Returns structured summary + top_domains + per_query, plus a rendered Markdown report (include_markdown=true) suitable for a public page. Provide queries[] or a panel name. Same engine selection as check_citations.

Input Output Examples

Name	Type	Req	Description
brand_terms	array	–	Brand name variants to detect in answer text for sentiment (defaults to the domain's second-level label).
competitors	array	–	Optional competitor domains to surface explicitly in the share-of-voice table.
domain	string	yes	The domain you are measuring visibility for (e.g. automatelab.tech).
engine	string	–	AI engine to query. 'auto' picks the first configured key. Same selection as check_citations.
include_markdown	boolean	–	If true (default), include a rendered Markdown report under `markdown`.
max_results	integer	–	Max citations to pull per query.
panel	string	–	Name of a saved panel (see panel_track) to pull queries from. Provide this OR `queries`.
queries	array	–	Queries to run. Provide this OR `panel`. Each is sent to the AI engine via check_citations.

Name	Type	Req	Description
error	string	–	–
markdown	string	–	Rendered Markdown report. Present when include_markdown=true.
per_query	array	yes	–
summary	object	yes	–
top_domains	array	yes	Share-of-voice table, most-cited domains first.

No examples provided.

signals_ai_overview ~95

Check whether Google shows an AI Overview for a query, and which URLs it cites. Uses SerpAPI (free tier: 100/month). Set SERPAPI_KEY.

Input Output Examples

Name	Type	Req	Description
hl	string	–	Language code, default 'en'.
location	string	–	Location string, e.g. 'United States'. Affects AI Overview eligibility.
query	string	yes	Search query to check for Google AI Overview.

Name	Type	Req	Description
ai_overview_present	boolean	yes	Whether Google returned an AI Overview for this query.
ai_overview_text	string\|null	yes	AI Overview text, if present.
cached	boolean	yes	Whether the result was served from local cache.
fetched_at	string	yes	UTC ISO-8601 timestamp.
query	string	yes	The query checked.
sources	array	yes	URLs cited in the AI Overview.

No examples provided.

signals_answer_box ~150

Locate where each cited URL appears in the AI's raw answer text. Calls check_citations, finds the first mention of each citation's URL (or hostname) in raw_answer, and bins by char position into early/middle/late thirds. Surfaces whether your URL is cited up-front or buried near the end. Returns 'unknown' for engines without raw_answer (Bing, Brave).

Input Output Examples

Name	Type	Req	Description
engine	string	–	AI engine to query. web_rank engines (bing_serp, brave_serp) lack raw_answer and will return position 'unknown'.
max_results	integer	–	Max citations to locate.
query	string	yes	Search query whose AI answer to measure citation positions on.

Name	Type	Req	Description
answer_chars	number	yes	Total length of the engine's raw answer in characters.
buckets	object	yes	Count of citations per position bucket.
citations_total	number	yes	Total citations returned by the engine.
engine	string	yes	Engine used.
fetched_at	string	yes	UTC ISO-8601 timestamp.
note	string	–	–
positions	array	yes	Per-citation position in the AI answer.
query	string	yes	The query that was tested.

No examples provided.

signals_bing_gap ~190

Join Bing Webmaster Tools query stats with am_i_cited per query. Surfaces queries where the domain ranks well in Bing but is not cited in AI - the closest editorial wins. Bing's index backs Copilot/ChatGPT/Perplexity grounding, so a Bing rank gap is an LLM-citation gap. Requires BING_WEBMASTER_API_KEY (Bing Webmaster Tools -> Settings -> API Access).

Input Output Examples

Name	Type	Req	Description
domain	string	yes	Domain to analyze, e.g. 'automatelab.tech'. Used for the citation check.
engine	string	–	AI engine for the citation check.
queries	array	yes	Queries to cross-reference. 1-20 per call.
site_url	string	–	Verified Bing Webmaster site URL. Defaults to 'https://<domain>/'. Bing uses the https origin WITH a trailing slash, NOT the sc-domain: form GSC uses.

Name	Type	Req	Description
closest_wins	array	yes	Queries where domain ranks in Bing top-10 but is not AI-cited (the editorial gap).
domain	string	yes	Domain analyzed.
engine	string	–	Engine used for the citation check.
rows	array	yes	Per-query Bing rank + AI citation cross-reference.
site_url	string	yes	Bing Webmaster siteUrl used (https origin with trailing slash).

No examples provided.

signals_gsc_gap ~223

Join Google Search Console performance with am_i_cited per query. Surfaces queries where the domain ranks well in Google but is not cited in AI - the closest editorial wins. Requires GCP service account creds (credentials_path or GOOGLE_APPLICATION_CREDENTIALS env).

Input Output Examples

Name	Type	Req	Description
credentials_path	string	–	Path to GCP service account JSON. Defaults to env GOOGLE_APPLICATION_CREDENTIALS.
domain	string	yes	Domain to analyze, e.g. 'automatelab.tech'. Used both for the GSC site URL and the citation check.
end_date	string	yes	ISO date for GSC range end, e.g. '2026-05-01'.
engine	string	–	AI engine for the citation check.
queries	array	yes	Queries to cross-reference. 1-20 per call.
site_url	string	–	Override the GSC siteUrl. Defaults to 'sc-domain:<domain>'.
start_date	string	yes	ISO date for GSC range start, e.g. '2026-04-01'.

Name	Type	Req	Description
closest_wins	array	yes	Queries where domain ranks in Google top-10 but is not AI-cited (the editorial gap).
domain	string	yes	Domain analyzed.
engine	string	–	Engine used for the citation check.
range	object	yes	GSC date range.
rows	array	yes	Per-query GSC + AI citation cross-reference.
site_url	string	yes	GSC siteUrl used.

No examples provided.

signals_wikipedia ~178

List Wikipedia articles that reference the given domain. Read-only. One HTTPS GET to the Wikipedia API (en.wikipedia.org/w/api.php?action=query&list=exturlusage). No auth required; no API keys; no rate limits beyond Wikipedia's public API fair-use policy (~1 request/second). Returns article titles and URLs. Wikipedia backlinks are the highest-lift signal for LLM training corpora — a domain cited from Wikipedia is far more likely to appear in AI training data and citation pools. Use lang to query non-English Wikipedias.

Input Output Examples

Name	Type	Req	Description
domain	string	yes	Domain to search for, e.g. 'automatelab.tech' (without protocol).
lang	string	–	Wikipedia language subdomain, e.g. 'en', 'de', 'fr'.
limit	integer	–	Maximum mention rows to return.

Name	Type	Req	Description
domain	string	yes	Domain that was searched.
fetched_at	string	yes	UTC ISO-8601 timestamp.
lang	string	yes	Wikipedia language subdomain used.
mentions	array	yes	List of Wikipedia articles that cite the domain.
total	number	yes	Number of Wikipedia articles referencing this domain.

No examples provided.

Install

How do I install the Citation Intelligence MCP server?

Citation Intelligence runs locally as an npm package, launched with npx -y @automatelab/citation-intelligence. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

npm · @automatelab/citation-intelligence

Client

Showing Claude. Snippets for every client (markdown)

# add to Claude Code

claude mcp add automatelab-tech-citation-intelligence -- npx -y @automatelab/citation-intelligence

Common questions

What is the Citation Intelligence MCP server?

Citation Intelligence is an MCP server listed in the public MCP registry as io.github.AutomateLab-tech/citation-intelligence. Check what Perplexity, Claude, ChatGPT, Gemini, and Google AI Overviews cite for any query. This page covers its npm package (@automatelab/citation-intelligence).

Is the Citation Intelligence MCP server safe to use?

Citation Intelligence scores 81 out of 100 on VerifyMCP. We recorded 38 known advisories against it as of 5 November 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the Citation Intelligence MCP server expose?

Citation Intelligence exposes 26 tools: citations_check, domain_am_i_cited, signals_ai_overview, domain_cited_for, citations_predict, and 21 more. Their descriptions and schemas cost roughly 4,260 tokens of context every time the server is loaded.

Is the Citation Intelligence MCP server still maintained?

Citation Intelligence is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the Citation Intelligence MCP server under?

Citation Intelligence declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

On this page

Handy links

Scoring key

80+ high trust
60–79 medium
below 60 low

How we score

Badge

Put this score in your README. The image is served from a stable URL, updates when the score does, and links back to the evidence on this page. It shows nothing that is not already published here.

Score Verified Plain

The two-cell badge: our name, and this channel's current score out of 100.

Markdown

 [![VerifyMCP trust score for Citation Intelligence](https://verifymcp.io/badge/automatelab-tech-citation-intelligence/automatelab-citation-intelligence.svg)](https://verifymcp.io/servers/automatelab-tech-citation-intelligence/automatelab-citation-intelligence)

HTML

 <a href="https://verifymcp.io/servers/automatelab-tech-citation-intelligence/automatelab-citation-intelligence"><img src="https://verifymcp.io/badge/automatelab-tech-citation-intelligence/automatelab-citation-intelligence.svg" alt="VerifyMCP trust score for Citation Intelligence" height="20"></a>

A single cell stating that the server is listed here. Carries no number.

Markdown

 [![VerifyMCP trust score for Citation Intelligence](https://verifymcp.io/badge/automatelab-tech-citation-intelligence/automatelab-citation-intelligence.svg?variant=verified)](https://verifymcp.io/servers/automatelab-tech-citation-intelligence/automatelab-citation-intelligence)

HTML

 <a href="https://verifymcp.io/servers/automatelab-tech-citation-intelligence/automatelab-citation-intelligence"><img src="https://verifymcp.io/badge/automatelab-tech-citation-intelligence/automatelab-citation-intelligence.svg?variant=verified" alt="VerifyMCP trust score for Citation Intelligence" height="20"></a>

The score alone, tier-coloured, for a badge row that is already crowded.

Markdown

 [![VerifyMCP trust score for Citation Intelligence](https://verifymcp.io/badge/automatelab-tech-citation-intelligence/automatelab-citation-intelligence.svg?variant=plain)](https://verifymcp.io/servers/automatelab-tech-citation-intelligence/automatelab-citation-intelligence)

HTML

 <a href="https://verifymcp.io/servers/automatelab-tech-citation-intelligence/automatelab-citation-intelligence"><img src="https://verifymcp.io/badge/automatelab-tech-citation-intelligence/automatelab-citation-intelligence.svg?variant=plain" alt="VerifyMCP trust score for Citation Intelligence" height="20"></a>

Score history · last 30 days

7 Oct 5 Nov

Day	Score
7 Oct	78
12 Oct	80
13 Oct	34
14 Oct	81
15 Oct	78
16 Oct	79
17 Oct	81
18 Oct	81
19 Oct	81
20 Oct	81
21 Oct	81
22 Oct	81
23 Oct	81
24 Oct	81
25 Oct	81
26 Oct	80
27 Oct	81
28 Oct	81
29 Oct	81
30 Oct	81
31 Oct	81
1 Nov	81
2 Nov	80
3 Nov	81
4 Nov	81
5 Nov	81