Introduction
Personal Knowledge MCP Server - Turn your documents into Claude's memory
textrawl
textrawl is a Personal Knowledge MCP Server that gives Claude access to your documents, emails, notes, and other knowledge. It uses hybrid search combining semantic understanding with keyword matching to find the most relevant content.
What is MCP?
The Model Context Protocol (MCP) is an open standard for connecting AI assistants to external data sources and tools. Adopted by Anthropic for Claude and donated to the Linux Foundation's Agentic AI Foundation, MCP enables:
- Tool Use: Claude can call functions to search, retrieve, and create content
- Context Sharing: Your documents become part of Claude's working knowledge
- Privacy: Data stays on your infrastructure, not uploaded to the cloud
Why textrawl?
Give Claude access to your personal documents, emails, notes, and knowledge. textrawl combines semantic understanding with keyword precision using Reciprocal Rank Fusion to deliver the most relevant results.
Hybrid Search
Combine semantic similarity with full-text keyword matching. Adjust weights to optimize for your use case.
Persistent Memory
Remember facts about people, projects, and concepts. Build a knowledge graph with relationships between entities. Track conversation context across sessions.
Proactive Insights
Automatically discover cross-source connections, recurring themes, and outliers in your knowledge base after bulk imports.
Multi-Format Support
Import MBOX emails, HTML pages, PDFs, DOCX files, and more. Convert once, search forever.
MCP Native
Native Model Context Protocol integration. Works with Claude Desktop, Cursor IDE, and any MCP client.
Privacy First
Self-hosted on your infrastructure. Your documents never leave your control.
Quick Start
MCP Tools
textrawl exposes 18 tools via MCP:
Document Tools
| Tool | Purpose |
|---|---|
search | Hybrid semantic + full-text search with optional memory/conversation fusion |
get_document | Retrieve full document content |
list_documents | Browse documents with pagination |
update_document | Update document title and tags |
add_note | Create notes with automatic embedding |
Memory Tools
| Tool | Purpose |
|---|---|
remember_fact | Store facts about entities with semantic embeddings |
build_knowledge | Store multiple facts and relations in a single batch call |
query_memory | Query the memory graph (search, entity, or list modes) |
relate_entities | Create relationships between entities |
forget_entity | Delete entity and associated memories |
extract_memories | Extract entities and facts from text via LLM |
Conversation Tools
| Tool | Purpose |
|---|---|
save_conversation_context | Save conversation summary and turns for recall |
query_conversations | Query past conversations (search, get, or list modes) |
delete_conversation | Delete a conversation session |
Insight Tools
| Tool | Purpose |
|---|---|
get_insights | View discovered patterns and connections |
discover_connections | Trigger insight scan across knowledge base |
dismiss_insight | Dismiss an insight from the queue |
Stats
| Tool | Purpose |
|---|---|
get_stats | Statistics across knowledge, memory, conversations, and insights |
Architecture
Learn more about hybrid search →
Next Steps
- Quick Start - Get running in 5 minutes
- Installation - Detailed setup guide
- CLI Tools - Import your documents