"Connecting to SEC EDGAR MCP using Bedrock Models" matching MCP servers:

Provides typed, read-only tools over SEC EDGAR for company lookup, filing lists, annual XBRL financial facts, and 10-K/10-Q item sections. Every result carries a source URL so answers can be grounded in and cite the underlying 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.

A free MCP server for stock research combining Finviz screening and SEC EDGAR filings, offering 24 tools for fundamental analysis, insider trades, and financial data without paid subscriptions.

MCP server for SEC EDGAR data, providing company search, financial statements, XBRL concepts/frames, filings, Form 4 insider trades, and 13F filings via User-Agent authentication.

It enables AI assistants (Claude, Cursor, etc.) to access SEC EDGAR data through 6 structured tools — from discovering available filings to keyword-searching within their pages.

Enables agents and people to run local SEC research queries against EDGAR or demo fixtures, returning verifiable financial data, filing text, charts, and evidence packets with explicit source and coverage.

Enables efficient SEC EDGAR filing access by saving filings to disk, returning file paths to avoid context overflow, and providing Bloomberg Terminal-style formatted output for selective reading and search.

Enables deep analysis of SEC EDGAR filings through universal company search, document content extraction, and advanced filing search capabilities. Provides AI-ready access to business descriptions, risk factors, financial statements, and full-text search across any public company's SEC documents.

Enables querying SEC Form N-PORT data to find which mutual funds and ETFs hold a given security, view a fund's reported portfolio positions, and check data coverage and scope.

Enables AI agents to look up facts about notable machine-learning models — organization, release date, parameter count, training-compute (FLOP) estimate, hardware and accessibility — by name, and to search or aggregate them by organization, domain, year, or compute threshold. Supports filtering the dataset newest-first and producing per-year training-compute trends, keylessly and without authentication.

MCP server providing SEC EDGAR signal intelligence — insider trading (Form 4), 13F holdings, filing velocity, activist risk flags, and multi-company comparisons. Already on the official MCP Registry, awesome-mcp-servers (PR #5664 pending), and Apify Store with three-tier pay-per-event pricing. MIT license, TypeScript, comprehensive README.

55 Concordance-tested financial models with published specs; responses cite assumptions and sources.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.

Enables an AI coding agent to take a research paper from arXiv, record its claims, build and run an implementation, measure the results, and receive a verdict for each claim. Every action is kept in a hash-chained evidence log, so the generated code folder and reproduction report can be checked without trusting the agent.

Ask a research question; in seconds get ranked companies, vetted 10-K/10-Q passages and financials.

Exposes 26 structured analytical tools over Climate Finance Update datasets, enabling fund-level financial analysis, portfolio aggregations, and data quality diagnostics without requiring the client to write data access code.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Enables SEC EDGAR financial research, analysis, valuation, and chart data generation through natural language.

Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.

Enables MCP clients to discover and invoke domain-specialized tools for humanitarian emergency response, public health, research synthesis, grant proposals, human rights monitoring, maternal health, and SOP synthesis. It supports JSON-RPC 2.0 over Streamable HTTP for structured, privacy-conscious field outputs and voice-friendly summaries.

Presents a plausible, tool-rich workspace surface — file reading, credential listing, command execution, database queries, and configuration retrieval — that returns only synthetic results while logging every connection, tool call, and argument received. It enables researchers to measure what MCP clients and agents actually do when handed dangerous-sounding tools, including whether they follow injected instructions or complete a retrieve-then-use credential chain.

Enables searching and retrieving UK research grants, award values, institutions, and publications from the UKRI Gateway to Research API without authentication.

Provides tools to interact with the OpenCTI platform, including checking if a campaign exists.

Enables keyword analysis and search volume data through the Marketing Miner API, connecting marketing intelligence tools to AI assistants like Cursor, Claude, and Windsurf.

Enables building targeted company lists from live job boards or SEC filings via the Apify actor, supporting role keywords, locations, and filing phrases.

Enables MCP clients to call OpenRouter Fusion, which queries a panel of models in parallel and synthesizes a single answer using a judge model, useful for research and critical decisions.

An open-source deep research MCP server that provides multi-source web search and synthesis with citations, enabling agents to perform citation-backed research using Qwen3-30B-A3B-Thinking and other models.