AI Agent Search Optimization
NPM · MCP-SERVER-AI-AGENT-SEARCH-OPTIMIZATION · SCANNED SEP 25
Audit AI search readiness, generate llms.txt drafts, and build GEO/AEO prompt matrices for websites.
Available components
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 Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 31 of 96 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency19
- Repository check failed: no source repository is declared. See how to fix → View diagnostics → Fail
- 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 98 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability62
- 50% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Partial
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 416 tokens (~69/item across 6 items; 3 tools + 3 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management87
- Stability observed for 26 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
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
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 4 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
How do I install the AI Agent Search Optimization MCP server?
AI Agent Search Optimization runs locally as an npm package, launched with npx -y mcp-server-ai-agent-search-optimization. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · mcp-server-ai-agent-search-optimization
claude mcp add seyitkaangunes-ai-agent-search-optimization -- npx -y mcp-server-ai-agent-search-optimization
{
"mcpServers": {
"seyitkaangunes-ai-agent-search-optimization": {
"command": "npx",
"args": [
"-y",
"mcp-server-ai-agent-search-optimization"
]
}
}
} {
"servers": {
"seyitkaangunes-ai-agent-search-optimization": {
"command": "npx",
"args": [
"-y",
"mcp-server-ai-agent-search-optimization"
]
}
}
} codex mcp add seyitkaangunes-ai-agent-search-optimization -- npx -y mcp-server-ai-agent-search-optimization
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"seyitkaangunes-ai-agent-search-optimization": {
"type": "local",
"command": [
"npx",
"-y",
"mcp-server-ai-agent-search-optimization"
],
"enabled": true
}
}
} openclaw mcp add seyitkaangunes-ai-agent-search-optimization --command npx --arg -y --arg mcp-server-ai-agent-search-optimization
mcp_servers:
seyitkaangunes-ai-agent-search-optimization:
command: "npx"
args: ["-y", "mcp-server-ai-agent-search-optimization"] {
"McpServers": {
"seyitkaangunes-ai-agent-search-optimization": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"mcp-server-ai-agent-search-optimization"
]
}
}
} assistant mcp add seyitkaangunes-ai-agent-search-optimization -t stdio -c npx -a -y mcp-server-ai-agent-search-optimization
{
"mcpServers": {
"seyitkaangunes-ai-agent-search-optimization": {
"command": "npx",
"args": [
"-y",
"mcp-server-ai-agent-search-optimization"
]
}
}
} 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.
- 25 Sept 26 +1
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 23 Sept 26 −2
- Security disclosure: unverified → fail ▼ functional
- Stability: pass → 0.80 functional
- 22 Sept 26 0
- Stability: 0.97 → pass security
- Security disclosure: fail → unverified ▼ functional
- 21 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 18 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.
- 16 Sept 26 −2
- Stability: pass → 0.80 functional
- 15 Sept 26 0
- Stability: 0.97 → pass security
- 14 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
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 25 Sept 2026 · Analysed npm/mcp-server-ai-agent-search-optimization@0.1.1
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 →
Dependencies 96 packages
| Packages resolved | 96 |
|---|---|
| Stale | 31 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
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 →
audit_site ~107
Audit a website URL for AI search readiness: crawler access, robots.txt, llms.txt, sitemap discovery, schema, visible text, and citation-readiness blockers.
| Name | Type | Req | Description |
|---|---|---|---|
| agents | array | – | Optional crawler user agents to check against robots.txt. |
| brand | string | – | Optional brand/entity name to check in crawlable page text. |
| format | string | – | Output format. Defaults to json. |
| url | string | yes | Website URL to audit. Only http and https URLs are supported. |
No output schema declared.
No examples provided.
build_llms_txt ~138
Generate a concise /llms.txt draft as a curated map for AI agents. This is not a ranking guarantee.
| Name | Type | Req | Description |
|---|---|---|---|
| fromSitemap | boolean | – | Whether to include a sample of URLs from /sitemap.xml. |
| links | array | – | Optional curated links. Relative URLs are resolved against the site origin. |
| name | string | yes | Brand, product, or website name. |
| site | string | yes | Website origin, e.g. https://example.com. |
| sitemapLimit | integer | – | Maximum sitemap URLs to include when fromSitemap is true. |
| summary | string | yes | One-sentence positioning summary for AI agents. |
No output schema declared.
No examples provided.
prompt_matrix ~150
Generate reusable AI visibility prompts for ChatGPT, Perplexity, Google AI Mode, and similar answer engines.
| Name | Type | Req | Description |
|---|---|---|---|
| audience | string | – | Target audience. Defaults to buyers. |
| brand | string | yes | Brand/entity name. |
| category | string | yes | Product, service, or market category. |
| competitors | array | – | Competitor names for comparison prompts. |
| format | string | – | Output format. Defaults to json. |
| location | string | – | Location for local-intent prompts. Defaults to the United States. |
| pains | array | – | Customer problems for problem-intent prompts. |
| surface | string | – | AI surfaces to track. Defaults to ChatGPT, Perplexity, Google AI Mode. |
No output schema declared.
No examples provided.
What is the AI Agent Search Optimization MCP server?
AI Agent Search Optimization is an MCP server listed in the public MCP registry as io.github.SeyitKaanGunes/ai-agent-search-optimization. Audit AI search readiness, generate llms.txt drafts, and build GEO/AEO prompt matrices for websites. This page covers its npm package (mcp-server-ai-agent-search-optimization).
Is the AI Agent Search Optimization MCP server safe to use?
AI Agent Search Optimization scores 75 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 25 September 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 AI Agent Search Optimization MCP server expose?
AI Agent Search Optimization exposes 3 tools: audit_site, build_llms_txt, prompt_matrix. Their descriptions and schemas cost roughly 395 tokens of context every time the server is loaded.
Is the AI Agent Search Optimization MCP server still maintained?
AI Agent Search Optimization is still listed as active in the MCP registry. We last reached this channel on 25 September 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 AI Agent Search Optimization MCP server under?
AI Agent Search Optimization declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.