"Companies Building Using MCP" matching MCP servers:

A template for building Model Context Protocol servers using Elysia and Bun runtime, enabling LLM clients like Claude Desktop and Cody to access custom tools, prompts, and data resources.

Processes documents, analyzes GitHub repositories, and researches companies using local Gemma3 AI to extract structured business insights for generating compelling case studies.

A lightweight framework for building and orchestrating AI agents through the Model Context Protocol, enabling users to create scalable multi-agent systems using only configuration files.

Enables building and querying knowledge graphs by ingesting documents into Neo4j using Gemini for entity extraction, and exposes MCP tools for graph health, document ingestion, and knowledge base querying.

A Compact Knowledge Graph MCP server providing pre-structured domain knowledge as a routing layer for agent stacks, enabling efficient structural queries (e.g., prerequisites, dependency chains) without hallucinations.

Enables searching and reading AVEVA Customer Support Portal knowledge base articles, including tech notes, known issues, and error-message diagnostics, to ground AI answers in support content not found in public documentation.

Provides MCP tools for web scraping, including smart fetching, proxy rotation, and browser rendering to bypass anti-bot challenges and render JavaScript-heavy sites.

Enables Claude and other MCP-compatible agents to process documents, extract structured data, detect PII, and export LLM-ready datasets through natural language tool calls.

Enables any MCP-aware LLM host to filter noisy text down to query-relevant sentences via a topic-conditioned relevancy classifier, reducing token spend before the model processes the full input.

Enables clients to interact with PipesHub data and functionality through MCP, including chat, search, record retrieval, directory browsing, sources, and agents.

Enables adding a cite-or-refuse answer box to your docs from your agent.

Provides AI assistants with real-time web search, reasoning, and research capabilities through Perplexity's Agent API and Search API, enabling tools for search, conversational Q&A, deep research, and advanced reasoning.

SEC EDGAR filing MCP for equity research agents: search 10-K/10-Q/8-K with CompanyFacts metrics, preview a free sample, and purchase full structured JSON via x402 USDC on Polygon. Public endpoint on xpay.tools.

Indexes your project's markdown documentation and exposes it to AI agents via local hybrid search (lexical + semantic) with progressive disclosure tools.

MCP server for the full Pāli Tipiṭaka — ~444,000 segments at parity with SuttaCentral (Sutta + Vinaya + Abhidhamma). Hybrid search, full-sutta fetch with cross-references, segment-aligned translation comparison, and Pāli word lookup. Offered as Dhamma Dāna.

A zero-cost, fully local MCP server that grounds AI assistants in verified web text, reducing hallucinations by ~80% by forcing answers only from fetched sources.

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

Low-token MCP server for HPE Networking automation, enabling search of Aruba/HPE docs, OpenAPI details, Central health checks, troubleshooting workflows, configuration management, and guarded ArubaOS 8 migrations and GreenLake Platform operations across platforms like Aruba Central, ClearPass, Mist, and Apstra.

Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.

Gives local and cloud LLMs live web grounding as four MCP tools: web_search, fetch, deep_search (a token-capped, cited evidence pack sized to a small context window), and research (an agentic search-and-read loop). Flat monthly pricing, no query content stored.