"Île-de-France Mobilités" matching MCP servers:

MCP server exposing memory search, index, and stats tools for agents, with honesty guards to prevent re-litigation of settled decisions.

Provides persistent memory for AI coding agents via MCP, enabling teams to share and recall facts across sessions. Automatically captures, classifies, and curates knowledge from supported transcript sources.

Python MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.

A Model Context Protocol server that allows Large Language Models to interact with Astra DB databases, providing tools for managing collections and records through natural language commands.

Persistent AI memory server with 3-layer hybrid search (vector + FTS5 + keyword), confidence scoring via Reciprocal Rank Fusion, episodic/profile memory, and 16 tools. Zero LLM dependency. Works standalone with Claude Desktop and Claude Code. MIT licensed.

Connects AI assistants to a persistent memory engine with Neo4j knowledge graph and ProMem extraction, enabling long-term context and associative memory across chats and workspaces.

A long-term memory MCP server for AI agents that stores memories (facts, decisions, etc.) in a single SQLite database with hybrid search and full edit history, ensuring consistency across sessions.

An MCP server that streams K-line (candlestick) data from decentralized exchanges (DEXs) to power your AI agents and workflows.

A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.

Enables storing and retrieving semantic memories using LanceDB vector database, with tools to add memories and search by similarity.

Gives AI agents a local-first, persistent memory backed by a single SQLite file, letting them save decisions, preferences, and facts, then recall them by meaning or keyword across sessions and projects. Exposes tools for loading pinned context, searching, adding, updating, listing, and deleting memories, so agents stop forgetting between sessions.

Persistent AI memory server with 3-layer hybrid search (vector + FTS5 + keyword), confidence scoring via Reciprocal Rank Fusion, episodic/profile memory, and 16 tools. Zero LLM dependency. Works standalone with Claude Desktop and Claude Code. MIT licensed.

A knowledge base MCP server backed by Qdrant vector database with local embeddings for semantic search and document management.

RAGX MCP Server enables retrieval-augmented generation with document ingestion, hybrid search, and agentic answering using Claude, exposing tools for querying, searching, and managing documents.

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.

Enables AI agents to store and retrieve persistent memory through MCP over HTTP (Streamable HTTP and compatible SSE) or stdio.

A comprehensive MCP server for time tracking, project management, and AI-powered memory storage using semantic search. It enables users to log time, manage client billing, and capture shared or personal ideas through integrated tools and team collaboration features.

Turns your Readwise library into a blazing-fast semantic search engine with a streaming MCP server for LLM clients, supporting vector search, nightly syncs, and deployment on serverless platforms like Vercel.

Provides tools for semantic search, CRUD, verification, and reindexing of documents in a local vector-based knowledge base, usable via HTTP or stdio.

An MCP server that enables AI assistants to directly interact with Elasticsearch for searching, aggregating, and retrieving documents from indices, supporting full-text search, semantic search, and various query modes.

Provides a shared local memory MCP server so multiple coding agents can store, retrieve, and attribute memories across sessions. It enables agents to recall project knowledge and past fixes with provenance.

This MCP server provides evidence-based advice on vector database backends by retrieving measured benchmarks and operational traps, enabling you to ask questions and compare backends through natural language.

Enables reading and writing to a Pinecone vector index, including semantic search, document management, and stats retrieval.

Enables agents to interact with DataStax Astra DB databases, including exploring schemas, running vector and hybrid searches, and safely modifying data with confirmation.

A lightweight vector-based memory system for AI agents with tools to store, semantically search, and delete memories, using your own embedding model.

Universal MCP server for readonly-first access to Oracle, SQL Server, PostgreSQL, MySQL/MariaDB, SQLite, MongoDB, and Qdrant vector search.

Enables semantic search and knowledge management for local LLM clients through MCP, using locally embedded vectors stored in Qdrant.

MCP server for interacting with MariaDB databases, supporting standard SQL operations and optional vector/embedding search.

A universal database gateway implementing the Model Context Protocol, enabling MCP-compatible clients to connect, explore, and manage multiple databases with advanced features like OAuth2 authentication, health checks, and SQL optimization.

Enables local vector database operations with a Pinecone-compatible API, supporting exact and approximate search, metadata filtering, and semantic text queries over MCP.