TxtAI Assistant MCP MCP Server

Model Context Protocol (MCP) server implementation for semantic vector search and memory management using TxtAI. This server provides a robust API

Local serverstdioPython

What is the TxtAI Assistant MCP MCP server?

TxtAI Assistant MCP MCP server exists for a simple reason — assistants are far more useful when they can act on TxtAI Assistant MCP directly instead of describing what you should do. Model Context Protocol (MCP) server implementation for semantic vector search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memories with semantic vector database.

What you get

We extend txtai's capabilities by integrating it with the Model Context Protocol (MCP), enabling AI assistants like Claude and Cline to leverage its powerful semantic search capabilities. Special thanks to the txtai team for creating such a powerful and flexible tool.

  • 🔍 Semantic search across stored memories
  • 💾 Persistent storage with file-based backend
  • 🏷️ Tag-based memory organization and retrieval
  • 📊 Memory statistics and health monitoring
  • 🔄 Automatic data persistence
  • 📝 Comprehensive logging

Setting it up

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

Configuration and credentials

  • Python 3.8 or higher - pip (Python package installer) - virtualenv (recommended)

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the txtai assistant mcp mcp server does with a few real requests.

Choosing this one

Among the knowledge and memory options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by rmtech1; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Configuration

  • Python 3.8 or higher - pip (Python package installer) - virtualenv (recommended)

Frequently asked questions

It integrates the txtai semantic search engine with the Model Context Protocol, allowing AI assistants like Claude and Cline to directly store and search memories using MCP tools while benefiting from txtai’s neural search, zero‑shot classification, and multi‑language support.