Agent evidence
PYPI · AGENT-EVIDENCE-MCP
Offline, read-only tools that verify AI claims against evidence and replay conformance vectors.
Available components
Last scanned (22 hours ago)
Scores higher than 86% of PyPI servers
Category Security
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 Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs setuptools.build_meta at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 1 of 37 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency100
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to probityai/probity). View diagnostics → Pass
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 3 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability55
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 402 tokens (~44/item across 9 items; 9 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management53
- Stability observed for 16 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- 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 9 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 10 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Checks we ran (16)
- Malware scan
- Known CVEs
- Install scripts
- Dependency health
- Source repository
- Provenance
- License
- Maintenance
- Security disclosure
- Schema quality
- Stability
- Tool coverage
- Injection markers
- Destructive annotations
- Judged manipulation
- MCP protocol
Does not apply to this package (2)
- Endpoint SecurityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
- Transport & ReachabilityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
The score does not measure everything. What the score does not measure →
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.
- 4 Nov 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 47 to 50. That category is still filling its 30-day observation window: 14 days of observed history at the previous scan, 15 at this one. The score rises as the window fills, whether or not the server changes.
- 2 Nov 26 +32
- Injection markers: unverified → pass ▲ security
- Tool coverage: unverified → 100 ▲ functional
- Stability: unverified → 0.43 ▲ functional
- MCP protocol: unverified → pass ▲ functional
- 1 Nov 26 −30
- Stability: 0.37 → unverified ▼ security
- Tool safety: pass → unverified ▼ security
- The attested source repository moved: probityai/agent-evidence-mcp → probityai/probity security
- Capabilities: pass → unverified ▼ functional
- Tool coverage: 100 → unverified ▼ functional
- Security disclosure: fail → pass ▲ functional
- First check of Schema quality: unverified functional
- Package version: 0.2.4 → 0.2.5 functional
- 30 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 30 to 33. That category is still filling its 30-day observation window: 9 days of observed history at the previous scan, 10 at this one. The score rises as the window fills, whether or not the server changes.
- 29 Oct 26 +11
- Provenance: fail → unverified ▼ security
- Provenance: fail → pass ▲ security
- The attested source repository moved: probityai/agent-evidence-mcp security
- Package version: 0.2.0 → 0.2.4 functional
- Package version: 0.2.0 → 0.2.3 functional
- 27 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.
- 25 Oct 26 +2
- Stability: unverified → 0.17 ▲ functional
- 21 Oct 26 +15
- Malware scan: unverified → pass ▲ security
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 pypi/agent-evidence-mcp@0.2.5
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | probityai/probity |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/probityai/probity/.github/workflows/release.yml@refs/tags/agent-evidence-mcp-v0.2.5 |
| Rekor log index | 3629912955 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:f071939b04933477c56b532a1db7deab93b914c7e4017609ce0389c5e2f63326 |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | Known build tool | setuptools.build_meta |
Background: Why install scripts are a supply-chain risk →
Dependencies 37 packages
| Packages resolved | 37 |
|---|---|
| No linked repository | 1 |
| 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 →
canonicalize_json Canonicalize JSON under RFC 8785 ~45
Admit one JSON document and return its RFC 8785 canonical bytes, with the jcs-admit crate.
| Name | Type | Req | Description |
|---|---|---|---|
| document | string | yes | – |
| profile | string | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
check_artifact_digest Check an artifact digest against a document ~51
Check that an artifact has a digest a TEA, CycloneDX or in-toto document names.
| Name | Type | Req | Description |
|---|---|---|---|
| artifact_base64 | – | – | – |
| artifact_text | – | – | – |
| document | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
explain_vector Explain one conformance vector ~41
Return one vector: its manifest entry, the conditions it tests, and its input bytes.
| Name | Type | Req | Description |
|---|---|---|---|
| corpus | string | – | – |
| vector_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_vector_corpora List conformance vector corpora ~27
Name every shipped corpus with its suite revision and vector counts where it declares them.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
lookup_term Look up a vocabulary term ~32
Look a term up in the released vocabulary by exact key; otherwise suggest close keys.
| Name | Type | Req | Description |
|---|---|---|---|
| term | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
run_vectors Replay a conformance vector corpus ~46
Replay one corpus with the bundled reference verifier; per-vector rows come back in pages.
| Name | Type | Req | Description |
|---|---|---|---|
| corpus | string | – | – |
| limit | integer | – | – |
| offset | integer | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
verify_claim Verify a claim against evidence ~43
Decide one claim against evidence bytes the caller supplies, with probity-verify.
| Name | Type | Req | Description |
|---|---|---|---|
| artifacts | – | – | – |
| case | object | yes | – |
| policy | object | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
verify_dsse Verify a DSSE envelope ~51
Verify a DSSE envelope against Ed25519 keys the caller trusts, with the dsse crate.
| Name | Type | Req | Description |
|---|---|---|---|
| envelope | string | yes | – |
| threshold | integer | – | – |
| trusted_keys | array | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
verify_sample Run a bundled sample claim ~30
Run a bundled sample claim: contradicted, not_established or supported.
| Name | Type | Req | Description |
|---|---|---|---|
| scenario | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
How do I install the Agent evidence MCP server?
Agent evidence runs locally as a PyPI package, launched with uvx agent-evidence-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · agent-evidence-mcp
claude mcp add probityai-agent-evidence-mcp -- uvx agent-evidence-mcp
What is the Agent evidence MCP server?
Agent evidence is an MCP server listed in the public MCP registry as io.github.probityai/agent-evidence-mcp. Offline, read-only tools that verify AI claims against evidence and replay conformance vectors. This page covers its PyPI package (agent-evidence-mcp).
Is the Agent evidence MCP server safe to use?
Agent evidence scores 83 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. Its build provenance is signed and verified. 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 Agent evidence MCP server expose?
Agent evidence exposes 9 tools: verify_claim, verify_sample, list_vector_corpora, run_vectors, explain_vector, and 4 more. Their descriptions and schemas cost roughly 366 tokens of context every time the server is loaded.
Is the Agent evidence MCP server still maintained?
Agent evidence 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 Agent evidence MCP server under?
Agent evidence declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.
What did VerifyMCP test on the Agent evidence MCP server?
VerifyMCP ran 16 checks on Agent evidence, covering Malware scan, Known CVEs, Install scripts, Dependency health and 12 more. Endpoint Security and Transport & Reachability do not apply to a PyPI package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.