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Offline, read-only tools that verify AI claims against evidence and replay conformance vectors.
About
Offline, read-only tools that verify AI claims against evidence and replay conformance vectors.
Security Report
Valid MCP server (1 strong, 2 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
6 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-probityai-agent-evidence-mcp": {
"args": [
"agent-evidence-mcp"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
agent-evidence-mcp
An offline, read-only MCP server that decides whether a claim about an AI system holds against evidence bytes you supply, and replays the agent-evidence conformance vectors.
It's for agent builders, auditors and platform engineers who want their assistant to check evidence instead of trusting a report.
Install the released package: pip install agent-evidence-mcp==0.2.0. It pins probity-verify==0.1.1, agent-evidence-vectors==0.23.0, agent-evidence-vocabulary==0.6.0, agent-evidence-admission==0.1.2 and jcs-admit==0.1.0 exactly. The last one carries the jcs-admit and dsse Rust crates as wheels.
Quick start
Add it to Claude Code, then ask the assistant to run the sample claim:
claude mcp add agent-evidence -- uvx agent-evidence-mcp@0.2.0
Or install the Claude Code plugin: /plugin install agent-evidence --marketplace probityai/agent-evidence-mcp.
Or call a tool from Python, with no client installed beyond the package:
uvx --from agent-evidence-mcp==0.2.0 python - <<'PY'
import asyncio
from mcp.client import Client
from mcp.client.stdio import StdioServerParameters
async def main():
async with Client(StdioServerParameters(command="agent-evidence-mcp")) as client:
result = await client.call_tool("verify_sample", {"scenario": "contradicted"})
print(result.structured_content["decision"], result.structured_content["reason"])
asyncio.run(main())
PY
It prints:
contradicted selected_span_missing_from_record
A passage the report quotes is missing from the source capture, so the claim is contradicted. Use supported or not_established as the scenario for the other two decisions.
Tools
Nine tools, all read-only, offline and bounded: verify_claim, verify_sample, list_vector_corpora, run_vectors, explain_vector, lookup_term and check_artifact_digest, canonicalize_json and verify_dsse. Nothing is fetched, written or sent.
Status
Version 0.2.0. The tests run every tool through a real MCP client against the shipped corpus, and a mutation check confirms they fail when a tool's output is broken.
Documentation
| page | read it for |
|---|---|
| Tools | every tool, its arguments and what it returns |
| Install | Claude Code, Gemini CLI, Docker and plain stdio |
| Agent guide | a short index for agents using the server |
| Changing the repository | the commands to run and what never to hand-edit |
License
Apache-2.0.
Reviews
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