A
license-
qualityD
maintenanceEnables Claude Desktop to search and query personal document collections (PDF, Word, Markdown, text) using semantic search and conversational AI with full context preservation across exchanges.
Last updated
MIT
llm-wiki-mcp
by quick-sort
This server allows you to manage and interact with AI-powered wiki knowledge bases by ingesting documents and querying them with natural language.
Ingest documents (
ingest): Add documents from local file paths or URLs into a named wiki. The server automatically extracts entities, concepts, and cross-references, building structured wiki pages (entity pages, concept pages, source pages, and synthesis pages) from the source material.Query knowledge bases (
query): Ask natural language questions against a named wiki and receive AI-synthesized answers with[[wikilinks]]citations drawn from ingested content.Manage multiple wikis: Organize knowledge into separate named wikis (e.g.,
my-research,project-docs), with new wikis created automatically on first ingest.Process diverse formats: Ingest markdown files, PDFs, URLs, and other document types.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@llm-wiki-mcpquery my-research wiki: what are attention mechanisms?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
llm-wiki-mcp
HTTP MCP server providing wiki knowledge base tools (query and ingest), powered by llm-wiki-agent skills via the Claude Agent SDK.
Architecture
MCP Client (Claude Code, etc.)
↓ HTTP / stdio
llm-wiki-mcp (FastMCP server)
↓ Claude Agent SDK (query())
Claude Code agent session
↓ auto-loaded skills
llm-wiki-agent (.claude/commands/)
↓ /wiki-ingest, /wiki-query
Wiki markdown files (entities, concepts, sources, syntheses)The MCP server is a thin layer. The actual knowledge extraction, entity/concept page creation, cross-referencing, and contradiction detection are all handled by the llm-wiki-agent skill running inside a Claude Agent SDK session.
Related MCP server: RAG MCP Server
Quick Start
# Install dependencies
uv sync
# Clone llm-wiki-agent skills
git clone --depth 1 https://github.com/SamurAIGPT/llm-wiki-agent.git skills/llm-wiki-agent
# Set your Anthropic API key
export ANTHROPIC_API_KEY=sk-ant-...
# Start the server (HTTP mode, default port 8080)
uv run llm-wiki-mcp
# Or use stdio mode
uv run llm-wiki-mcp --transport stdioTools
ingest
Ingest a document (file path or URL) into a named wiki. The llm-wiki-agent skill handles reading, converting, extracting knowledge, and building cross-referenced pages.
ingest(wiki_name="my-research", source="raw/papers/attention-is-all-you-need.md")
ingest(wiki_name="my-research", source="report.pdf")query
Query a wiki with a natural language question. The skill searches all wiki pages and synthesizes an answer with [[wikilinks]].
query(wiki_name="my-research", question="What are the main approaches to attention?")Docker
docker build -t llm-wiki-mcp .
docker run -e ANTHROPIC_API_KEY=sk-ant-... -p 8080:8080 -v ./wikis:/home/agent/wikis llm-wiki-mcpOptional: configure custom base URL or models:
docker run \
-e ANTHROPIC_API_KEY=sk-ant-... \
-e ANTHROPIC_BASE_URL=https://custom.anthropic.com \
-e ANTHROPIC_SMALL_FAST_MODEL=claude-haiku-4-20250514 \
-e ANTHROPIC_DEFAULT_SONNET_MODEL=claude-sonnet-4-20250514 \
-e ANTHROPIC_DEFAULT_OPUS_MODEL=claude-opus-4-20250514 \
-e ANTHROPIC_DEFAULT_HAIKU_MODEL=claude-haiku-4-20250514 \
-p 8080:8080 \
-v ./wikis:/home/agent/wikis \
llm-wiki-mcpMaintenance
–Maintainers
1dResponse time
–Release cycle
–Releases (12mo)
Commit activity
Resources
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