"Fluent Bit" matching MCP servers:

An MCP server that enables local BM25 search over 1C:Enterprise platform documentation, exposing identical tools via both stdio and streamable HTTP endpoints.

Enables deterministic, auditable retrieval over a document corpus by decomposing queries into subqueries, allocating recall budgets, and merging ranked results that are bit-reproducible from a recorded seed.

MCP server for RSS aggregation and LLM summarization, allowing users to fetch latest articles, search archives, and generate topic-specific digests via natural language.

An AI conversation management layer that enables creating chat sessions, persisting message history to GitHub, and performing semantic searches over past interactions. It supports multi-turn threading and context injection to integrate external memory sources into Claude conversations.

A provider-neutral MCP server that provides tools for managing skills, agents, references, and artifact memory in a local workspace.

A composable semantic memory layer that provides cross-project recall and session context using Qdrant and OpenAI embeddings. It enables users to securely store, search, and manage persistent memories with built-in secret scrubbing for privacy.

A production-ready foundation for building secure, observable MCP servers with built-in authentication, rate limiting, and reference tools like database-query and semantic-search.

Provides read-only RAG retrieval, document access, source auditing, status, and health checks for CUMCM optimization and decision modeling contexts.

A Model Context Protocol server that generates prompts based on Git repository content, including a command to generate PR descriptions from diffs.

Connects an LLM to specialized MCP servers via stdio, enabling authenticated GitHub repository, issue, file, and code operations alongside TF-IDF retrieval over employee PDF records and QA test-case generation and result validation. It exposes tools, a read-only resource, and reusable prompt templates so a client can discover and orchestrate multiple capabilities in one workflow.

Enables users to build and query a project-local literature database by ingesting papers from Semantic Scholar, PubMed, arXiv, and OpenAlex, caching open-access PDFs, extracting full text, ranking results, and exposing MCP tools for search, seeds, feedback, and pipeline status over stdio.

A custom Model Context Protocol implementation that integrates Perplexity AI with Claude Desktop, allowing users to access Perplexity's AI models for both single questions and multi-turn conversations.

This read-only MCP Server allows you to connect to Power BI XMLA data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables AI coding tools and developers to store, search, and supersede durable engineering discoveries with temporal validity, and to coordinate active work across sessions via MCP.

Enables AI assistants to build and query temporally-aware knowledge graphs from conversations and data. Supports adding episodes, searching entities and facts, and maintaining persistent memory across interactions.

Transforms any GitHub repository into a documentation hub for AI assistants, enabling access to up-to-date documentation and code to eliminate hallucinations. Supports repository-specific and dynamic endpoints with smart search capabilities.

A Model Context Protocol (MCP) server that provides AI-powered customer support using Cursor AI and Glama.ai integration.

Enables local AI inference for Claude and Cursor through 22 APIs, including summarization, translation, review, classification, RAG, and more, with all data processed on-device.

Fetch web pages into clean, RAG-ready Markdown with a verifiable provenance record — source URL, UTC fetch time, SHA-256 of the response body, redirect chain, and an extraction-fidelity metric. Writes WARC archives and honours robots.txt/ai.txt, so every document an agent reads can be re-verified and cited.

Transforms any GitHub repository or GitHub Pages site into a documentation hub for AI assistants using the Model Context Protocol. It allows AI tools to access real-time code and documentation to prevent hallucinations and provide accurate API usage examples.