knowledge-curator-mcp

knowledge-curator-mcp

A local, zero-cost MCP server that fact-checks your Markdown/Obsidian notes using a local LLM (via Ollama) and free sources like Wikipedia and DuckDuckGo, with no cloud API or API keys.

Category
Visit Server

README

knowledge-curator-mcp

A local, zero-cost MCP server that fact-checks your Markdown / Obsidian notes.

It uses a local LLM via Ollama to extract claims and judge them against free, key-less sources (Wikipedia + DuckDuckGo). No cloud API, no API keys, nothing leaves your machine except the public search queries.

Unlike naive fact-checkers that count search hits, this server has the LLM read each source and decide whether it supports, contradicts, or is insufficient for the claim.

Why local?

  • No cost — runs entirely on your own machine.
  • Private — your notes are never sent to a cloud LLM.
  • Good enough — a small instruct model (3–7B) is plenty for "does this evidence support this sentence?" entailment judgments.

Requirements

  • Node.js ≥ 18 (uses the global fetch)
  • Ollama running locally with an instruct model pulled:
ollama pull qwen2.5:3b   # default — ~1.9GB, strong instruction-following
# alternatives: qwen3.5:4b (better), qwen2.5:7b (best, ~4.7GB)

A general instruct model is recommended over a persona/style fine-tune: fact-checking needs neutral, accurate reading, not a personality.

Install & build

npm install
npm run build

Configure your MCP client

Add to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "knowledge-curator": {
      "command": "node",
      "args": ["/absolute/path/to/knowledge-curator-mcp/build/index.js"],
      "env": {
        "OLLAMA_MODEL": "qwen2.5:3b"
      }
    }
  }
}

Environment variables

Variable Default Description
OLLAMA_HOST http://localhost:11434 Ollama server URL
OLLAMA_MODEL qwen2.5:3b Any installed Ollama model
WIKI_LANG ja Wikipedia language edition (en, ja, ...)

Tools

Tool What it does
verify_claim Verify a single statement; returns a verdict + citations.
fact_check_document Extract & verify claims in a file; optional auto_fix inserts notes.
add_citations Fact-check a file and insert footnote citations for claims that need them.
scan_vault_for_issues Walk an Obsidian vault and report files with contradicted/uncited claims.
git_commit_corrections Commit corrected files to git.

Verdicts

Verdict Meaning
verified Evidence clearly supports the claim.
incorrect Evidence clearly contradicts it (a correction is suggested).
📝 needs_citation Plausible & on-topic, but evidence doesn't directly confirm.
unverifiable Evidence unrelated or insufficient.

Example

"Verify: 日本の首都は大阪である。"

**Verdict**: ❌ incorrect (90% confidence)
**Reasoning**: Evidence clearly contradicts the claim that '日本の首都は大阪である'.
**Sources**: Wikipedia: 大阪市, Wikipedia: 首都圏 (日本), ...
**Suggested correction**: 日本の首都は東京である。

How it works

note.md ──▶ [LLM extracts claims] ──▶ for each claim:
                                         ├─ Wikipedia search (intro extracts)
                                         ├─ DuckDuckGo instant answer
                                         └─ [LLM reads evidence → verdict + citation]

Limitations

  • Quality scales with the model. A 3B model occasionally produces a sloppy rationale; use qwen3.5:4b/qwen2.5:7b for tougher material.
  • Free sources are shallow: Wikipedia covers general/encyclopedic facts well, but niche or very recent claims will often come back unverifiable.
  • auto_fix edits files in place — keep your notes under version control.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured