Agenda Intelligence MD MCP server

<!-- mcp-name: io.github.vassiliylakhonin/agenda-intelligence-md -->

Agenda Intelligence MD

Agenda Intelligence MD is a deterministic evidence-packet linter and compliance orchestration engine for claim-backed AI output. It provides verifiable trust boundaries, guardrail enforcement, and evidence-readiness triage across A2A (Agent-to-Agent), MCP (Model Context Protocol), CLI / Python API, and Serverless Edge Workers (Cloudflare).

Core concepts

Agenda Intelligence MD is a deterministic evidence-packet linter for claim-backed AI output.

Give it claims, the source IDs each claim relies on, optional quotations, and the supplied source text. It returns broken references, quote mismatches, lexical-support gaps, unmatched numbers, claims that negate the source they cite, and the next reviewer actions.

It reports packet completeness, not whether a claim is true:

• not a factuality verifier;
• no autonomous live source retrieval;
• no authorization, approval, or compliance decision;
• human review is required for every result.

First run

Run the canonical synthetic packet from a source checkout:

git clone https://github.com/vassiliylakhonin/agenda-intelligence-md
cd agenda-intelligence-md
python -m venv .venv
.venv/bin/python -m pip install -e .
.venv/bin/agenda-intelligence check examples/evidence-packet/request.json

Expected shape:

packet_status=packet_complete claims=2 sources=1 factuality=not_assessed
  c1: packet_complete (lexical_support=supported, coverage=1.0)
  c2: packet_complete (lexical_support=supported, coverage=1.0)

Use JSON for an agent loop or CI pipeline:

.venv/bin/agenda-intelligence check examples/evidence-packet/request.json --format json
.venv/bin/agenda-intelligence check examples/evidence-packet/request.json --strict

--strict exits non-zero unless every claim is packet_complete.

Find where a claim could be supported, before deciding what it cites:

.venv/bin/agenda-intelligence discover examples/evidence-review/manifest.json

discover derives literal patterns from each claim — figures and quoted spans first, then content terms, rarest first — and matches every one against every source, reporting the line that matched. Nothing is sampled and no model is called, so it behaves the same on 40 sources and on 4,000. It names the sources a claim's own figures reach but it does not cite, and the ones it cites where not one pattern occurs. Candidates are places to look: nothing here verifies a claim, and a source that supports one in different words does not appear at all.

Review local source files without copying their full text into JSON:

.venv/bin/agenda-intelligence review examples/evidence-review/manifest.json \
  --out evidence-review.md --strict

The manifest keeps claims explicit and points to local UTF-8, Markdown, DOCX, or PDF sources. Paths are resolved inside the manifest directory. DOCX support uses the Python standard library; PDF extraction requires pip install -e ".[documents]". The command makes no network or model call and does not include source text in its JSON or Markdown result. See docs/evidence-review.md.

Install the pinned release without cloning the source and check your own packet:

pip install "agenda-intelligence-md==1.11.1"
agenda-intelligence check /path/to/evidence-packet.json --strict

Generate an interactive standalone HTML reviewer report from local documents:

Shortened. The full README is on GitHub.