"US Government Open Data API Aggregator (FEC, SEC, Congress, Lobbying, USAspending)" matching MCP servers:

MCP server for SEC EDGAR filing intelligence, providing tools for fetching, chunking/embedding, retrieval, and evaluation of filings.

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.

Enables AI agents to drive a user's own signed-in Google NotebookLM (Gemini Notebook) account through 51 MCP tools, covering notebook and source management, grounded chat with numbered citations, fast and deep research, and generating or downloading audio/video overviews, slide decks, quizzes, flashcards, mind maps, infographics, reports and data tables. It runs over stdio or streamable HTTP on localhost and sends progress notifications for long-running jobs.

Enables querying and analysis of SEC filing documents through natural language. Uses Pinecone vector search with document summarization to help users retrieve and understand financial filings for various companies.

Enables document Q&A with grounded citations using the official Gemini File Search API. Upload documents, create stores, and ask questions that return exact passage citations.

Enables agents to query a self-hosted, locally indexed web corpus through MCP tools for keyword, neural, or hybrid search, to fetch clean text from already-indexed URLs, and to discover pages similar to an indexed URL.

Enables AI assistants to manage notebooks, sources, notes, search content, and interact with AI models through Open Notebook.

Personal knowledge graph with 16 MCP tools. Auto-links, deduplicates, tracks themes, synthesizes insights.

MCP server providing access to US patent data (2000-2024) via Rememberizer's knowledge retrieval tools, enabling semantic search and document management for patent information.

Enables multiple MCP agents to read and write a single user-controlled, local-first fact layer under one user identity with explicit scopes, preserving sources, versions, permissions, and audit history. Supports structured memories such as preferences, facts, task state, and decisions, plus structured handoff capsules so one agent can resume another's work by task ID.

Enables MCP clients to list, search, and read SEC 10-K filings, returning relevant passages with company, fiscal year, section path, and SEC URL citations so answers can be grounded in source documents.

A self-hosted second brain MCP server that enables capturing thoughts with deduplication and semantic search using local embeddings and PostgreSQL with pgvector, all running on your own hardware.

Stores what AI agents learn — thoughts, decisions, session events and repo facts — in PostgreSQL with pgvector and serves it back through versioned MCP tools with hybrid vector-plus-full-text retrieval and budgeted context packs. Enables multiple agents to share one scoped, role-isolated long-term memory, with deliberate promotion of distilled candidates into durable memories.

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

Exposes a local SQLite-backed long-term memory to AI agents as MCP tools, letting them add conversations and documents, record dated facts with provenance, search and assemble context, and edit, inspect, or forget what was stored. It runs with your own embedding and LLM keys, so memories stay readable, exportable, and portable as plain markdown.

Gives Claude Code a persistent, fully local long-term memory by automatically capturing session activity, indexing past conversations, projects, scheduled tasks and Obsidian notes, and recalling relevant context through hybrid keyword-plus-semantic search with progressive disclosure. It also writes session handoffs that are injected into later sessions, so work resumes with prior decisions and next steps already in context.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

Gives Claude Code persistent, local-first project memory: it records sessions, compresses them into searchable observations and summaries, and injects a compact project brief plus prompt-time recall at session start. It also exposes tools for recalling observations and timelines, managing durable tasks and notes, and reading any project's context, all backed by a local SQLite file with compression run on a local LLM.

An MCP server for storing and retrieving thoughts, notes, and ideas with semantic vector search, enabling integration with Claude Desktop and other MCP clients.

Unified AI Agent SaaS Connector & Multi-Provider Gateway connecting to 1,000+ SaaS platforms, vector databases, and 500+ LLM models via MCP, REST API, and CLI.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

A persistent, cross-session knowledge base for AI agents that indexes session history into a searchable SQLite database with full-text search, enabling recall of past sessions, stored knowledge, and summaries.

Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2

Access to many public datasets right from your LLM application.

A semantic layer query engine with MCP support, enabling AI assistants to query structured data through natural language and declarative interfaces.

An MCP server that gives AI coding assistants access to up-to-date API documentation via RAG by crawling documentation sites, indexing them into a vector store, and enabling semantic queries.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.

Enables Claude to answer plain-English questions by listing and describing database tables, running read-only SQL queries, and searching a folder of policy documents.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Enables natural language querying of PostgreSQL via MCP, combining SQL, vector search, and knowledge graph with automatic routing and token-aware curation.