About mcp-verify-claim
mcp-verify-claim is a deterministic MCP server that attaches evidence to agent claims and assigns evidence tiers. It needs no LLM or network access, and helps prevent unverified operation results from being reported as facts.
Key features
- 01Assigns four evidence tiers to claims
- 02Returns TRUST, REVIEW, or DO-NOT-REPORT verdicts
- 03Scans for unsupported completion claims
- 04Provides status and evidence report templates
Use cases
- 01Check whether agent operation reports have evidence
- 02Prevent unrun tests from being reported as passing
- 03Review deployment or API status claims
MCP support
The MCP server exposes tools for claim tiering, claim checks, tier definitions, and report templates. Claims without evidence can be marked DO-NOT-REPORT.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEmcp-verify-claim
A Model Context Protocol (MCP) server that forces evidence-gated, honestly tiered claim reporting. Every claim an agent makes gets classified into an evidence tier (FACT / INFERENCE / SPECULATION / UNVERIFIED) with attached evidence — the antidote to the silent-unverified-claim failure mode ("pushed successfully", "the tests pass", "the API returned 200" — asserted without ever running the command).
Deterministic, no LLM, no network calls. Self-hostable, MCP-compatible with any agent (Claude Code, Cursor, Copilot, OpenClaw, Codex CLI).
Why it exists
The most common agent failure is not wrong reasoning — it's reporting a
plausible-sounding result that was never verified. mcp-verify-claim
installs a hard gate: no unverified claim can be reported as fact.
The pattern it fits (agent tooling that answers with evidence, not opinion)
When you give an agent access to real operations (edits, checks, rule evaluation, mutations) through MCP, the value is that it can answer with evidence instead of opinion — it ran the check, it saw the real state, it can prove what it did. But that only holds if the agent is forced to attach the evidence. A rules-and-checks surface ("is the module valid?", "did this state change slice apply?", "what actually changed?") is exactly the high-value case: each check produces a machine-verifiable result.
mcp-verify-claim is the gate that guarantees the agent reports the result with
its evidence attached (exit code, real read-back, actual HTTP status) and cannot
pass off a guess or an unrun step as truth. Pair it with any MCP surface that
exposes operations, and the agent's answers become auditable, line-by-line,
instead of plausible.
Tools
tier_claim(claim, evidence, verification_kind)— classify a claim into a tier + verdict (TRUST/REVIEW/DO-NOT-REPORT) + honest next-action.check_claim(claim)— deterministic scan for fabrication/hedging signals (completion-without-artifact, "the API returned", hedge words).report_templates()— the canonical STATUS / EVIDENCE / GAPS completion shape and the 6-step behavioral loop.tier_definitions()— the FACT / INFERENCE / SPECULATION / UNVERIFIED definitions.
Evidence tier (the core)
| Tier | Meaning | Verdict |
|---|---|---|
| FACT | Saw it in raw tool output (exit code, body, file read-back, HTTP status) | TRUST |
| INFERENCE | Deduced from facts; show the chain | REVIEW |
| SPECULATION | A guess; never report as truth | REVIEW |
| UNVERIFIED | No evidence produced | DO-NOT-REPORT |
Install & run
One command (recommended) — installs from the repo, no PyPI token needed:
uv tool install git+https://github.com/sudo-ai-git/mcp-verify-claim
mcp-verify-claim # run stdio server
mcp-verify-claim --http --port 8137 # or Streamable HTTP for remote use
Or with pipx: pipx install git+https://github.com/sudo-ai-git/mcp-verify-claim
Direct from source (fallback):
pip install mcp
python3 mcp_server.py
Claude Desktop / agent config
{ "mcpServers": {
"verify-claim": { "command": "mcp-verify-claim", "args": [] }
}}
Example
tier_claim("Successfully deployed", evidence="", verification_kind="")
--> tier UNVERIFIED, verdict DO-NOT-REPORT
signals: [high] completion claim without artifact
next: go get the evidence before reporting
tier_claim("Deploy is live", evidence="origin/main SHA==local HEAD, HTTP 200", verification_kind="read_back")
--> tier FACT, verdict TRUST
Part of a family
This is one of three deterministic, no-LLM agent-trust MCP servers by sudo-ai-git:
mcp-skill-sec— pre-install skill/security auditmcp-verify-claim— evidence-gated, honestly-tiered claim reporting (this repo)mcp-benchmark-hygiene— pytest config-leakage / eval-honesty detection
Sibling product: mcp-token-saver — token-cost proxy + analyzer for agent conversations (dedupes redundant tokens before they're billed; live-proven 74% cut). Discussion
Also in the family (a free CLI, not an MCP server): harness-audit — deterministic agent-eval / benchmark-grading hygiene audit that catches the same silent config-leakage mis-scoring class. Free lead-magnet; the same verification discipline, zero dependencies, auditable line-by-line.
License & provenance
MIT. Written by sudo-ai-git. Standalone behavioral-rigor tool; encodes no
proprietary method. MCP expression of the verify-before-claim agent skill.
Official MCP Registry metadata
mcp-name: io.github.sudo-ai-git/mcp-verify-claim
Hire a custom integration
Need this connected to your internal system (auth, logging, security-scan pass, hosted)? Open a custom-build request. MIT reference assets are free to use either way.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.