"Host Tracker MCP server endpoint" matching MCP servers:

Keyless local RAG over your own documents (ChromaDB) with traceable citations, exposed as MCP tools and a FastAPI endpoint.

It connects an agent to a PostgreSQL database so it can inspect schemas, run validated reads and writes, resolve fuzzy names via trigram search, and perform or store pgvector embedding searches. Vector and hybrid search operate through an OpenAI-compatible embeddings endpoint, letting agents query by text without handling embedding arrays.

An MCP server that gives AI assistants persistent memory using an OpenAI vector store, enabling saving and semantic searching of text memories across sessions.

Mem0-compatible persistent memory for AI agents - write facts once, recall them semantically in any session. Self-hostable open-source server, or managed cloud with a remote MCP endpoint at https://deepmem.dev/mcp.

Enables chat.z.ai agents to keep persistent vector memory, auto-enhance context, compress long content to save tokens, and orchestrate smart skills, with every session mirrored to the user's own private GitHub repository as a human-readable cloud database. Exposes these capabilities through a streamable HTTP MCP endpoint with 12 tools, resources, and prompt templates.

Enables venues to discover taste-matched acts and artists or agents to find fitting rooms and cities through Qloo's taste graph. It exposes booking-focused tools for agent use over a remote MCP endpoint.

Enables MCP clients to discover, list, and call browser-demo tools for SQL-like queries, vector and hybrid search, agent memory, and evidence-ledger operations over a stateless HTTP endpoint.

Enables routing of natural-language tasks to the best-matching skill in a local pool of SKILL.md files, using a two-stage bi-encoder retrieval plus pointwise reranking pipeline that runs entirely on your machine. Exposes tools for searching skills, fetching a full skill record, triggering incremental or forced reindexing, and inspecting index statistics over a loopback-hosted MCP endpoint.

Enables MCP clients to index code repositories and run AST-aware semantic and hybrid keyword search across files, commits and branches, returning relevant code snippets with expanded file context. It handles incremental re-indexing with local embeddings and Qdrant storage, and can serve either over stdio or as a bearer-token-protected HTTP endpoint for remote or containerized use.

Enables clients to inspect and operate many Redis deployments at once — standalone, Redis Cluster, or Sentinel-managed — through a single endpoint, with 54 tools grouped into core, data, JSON, search, pub/sub, and docs toolsets. It supports read-only and destructive-tool switches, per-cluster isolation, secret-backed passwords, bounded 15-second calls, and Streamable HTTP or stdio transport.

Enables semantic search over OpenAPI endpoint catalogs using FAISS and LangGraph, returning grounded technical recommendations for natural-language API queries.

Provides a unified MCP interface that proxies requests to multiple backend servers including memory/knowledge graph and vector database services. Enables seamless access to distributed MCP tools through a single endpoint with automatic routing, health monitoring, and retry logic.