"Y Combinator" matching MCP servers:

Provides a compiled knowledge substrate, extracting atomic claims from an append-only capture log and querying a bitemporal claim graph over MCP. Read-only by default, with opt-in writes for trusted sources.

Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.

Provides an MCP protocol interface for interacting with Elasticsearch 7.x databases, supporting comprehensive search functionality including aggregations, highlighting, and sorting.

缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台，致力于通过代理AI技术减少人力成本，高效高精度为用户提供分钟级接入的内容风控解决方案，破解安全威胁，提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel

Enables programming agents to retrieve internal R&D documentation with traceable, reproducible evidence through the MCP protocol, supporting multi-corpus routing and access control.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Self-hosted OAM memory with cited recall over your existing deployment. Local stdio adapter with six tools for recall, retaining interactions and documents, operation readiness, stored Profile reads and exact memory removal. Run with npx -y @rocke-dong/oam-mcp; requires Node.js 22 and your OAM user-scoped API key. Submitted by the OAM maintainer with AI assistance.

This read-only MCP Server allows you to connect to HCL Domino 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/).

This read-only MCP Server allows you to connect to Microsoft Excel data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for Microsoft Excel (https://www.cdata.com/drivers/excel/download/mcp).

This read-only MCP Server allows you to connect to Adobe Analytics 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 secure read-only access to Tencent Lexiang knowledge bases via MCP, including listing directories, RAG search, and reading entries.

This read-only MCP Server allows you to connect to SAP ByDesign data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

Enables users to access real estate property industry news daily and search a specialized knowledge base covering laws, regulations, company info, and more.

Enables querying of live organizational data (student records, outcomes, certifications, finances, donations, communications) via Claude using structured database queries and semantic search.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.

Enables AI agents to provide e-commerce customer service with product search, RAG-based FAQ answers, human handoff, and automated security auditing with a review workflow.

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

A persistent memory layer for Claude Code agents: five MCP tools (recall, remember, session, distill, status) over a markdown vault, SQLite FTS5 and an optional self-hosted Hindsight vector store, so an agent remembers facts, decisions and corrections across sessions.

Enables developers and AI agents to compress context, plan token budgets, rerank results, patch code, analyze ASTs and dependencies, isolate stack traces, compile polyglot types, solve deterministic math, schedule constraints, judge A/B tests, and diff agent memory checkpoints through 12 specialized tools.

Enables MCP clients to give AI agents a shared, persistent Graph-RAG memory backed by an Obsidian-native vault, with hybrid search, token-budgeted recall, and memory updates.

Provides AI agents with 12 real-time tools for search synthesis, grounded research dossiers, claim verification, citation generation, sentiment analysis, expert ranking, timeline creation, and competitive landscape mapping over Streamable HTTP or stdio.

Provides tools for searching Agent8 game development code examples and system prompts to assist in Agent8 SDK development.

Enables building a local, searchable knowledge base from YouTube videos, with research, transcript retrieval, and timestamped citations.

Enables AI agents to write, validate, and render high-quality PostScript by providing operator lookup, vetted PSlib fragments, cited reference search, and Ghostscript-based checking.

Enables AI assistants to search a library of over 20,000 open legal skills by keyword, by meaning, or a hybrid of both, filtering by jurisdiction, language, practice area, or tag. It also returns facet counts for the collection and retrieves the full text of any selected skill.

Hermetic memory for AI agents — one Rust binary, one SQLite file, zero network. Recall returns evidence with provenance or abstains: no code path for making things up.

Auditable long-term memory for coding agents: facts carry their evidence and full supersession history, so why explains where a belief came from and forget retires instead of deleting. Runs embedded on a keyless SQLite store (npx -y statecore-mcp) with optional LLM distillation and a self-hosted StateCore server mode.

Provides e-commerce customer support tools for order status, delivery, account, and policy questions, with RAG-grounded retrieval and strict authorization checks over mock data.

Enables AI agents to query verified-emissions knowledge graphs in natural language and validate data against supported standards, with metered billing and optional verified identity.

Enables coding agents to query a team knowledge base via MCP, performing semantic search and asking questions that return grounded, citation-backed answers from ingested documents.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.

Enables CI/CD failure triage for GitHub Actions by inspecting failed runs, classifying root causes with LLM assistance, retrieving relevant runbook guidance, estimating flakiness, and either preparing dry-run fix PRs or publishing structured diagnoses to Discord for human review.

Semantic code search for any MCP client: indexes local folders of code and docs and answers plain-language or code queries with matching passages, file paths, line ranges and scores. Embedding runs on the local CPU with the Motherlode code-search encoder, so no file content leaves the machine; the encoder downloads once from Hugging Face. Install: npx -y blackwindow-weave-mcp.

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

Persistent, consensus-validated institutional memory for AI agents. Gives LLMs real memory that survives across sessions - validated through BFT consensus, not just dumped to a file.

Memory for AI agents that keeps every claim with the source it came from, the date it was asserted, and a confidence you can re-weight per source, so your agent can say where a fact came from. Updates supersede or retract instead of overwriting, so you can replay what the store believed on any past date and review contradictions as lint findings.