"A server for conducting deep research" matching MCP servers:

An MCP server that exposes Gemini's Deep Research Agent for comprehensive web research.

A server that allows AI assistants to perform web searches using Perplexity's sonar-deep-research model with citation support.

An MCP server for deep research that performs search, scraping, synthesis, fact-checking, and persistent memory, enabling users to conduct comprehensive research tasks via Claude.

A Model Context Protocol server that performs comprehensive web research by combining Tavily Search and Crawl APIs to gather extensive information and provide structured JSON output tailored for LLMs to create detailed markdown documents.

Web search, clean page reading & one-call research dossiers for AI agents. No API key — your agent does the synthesis.

Enables deep research evidence synthesis and citation verification by generating structured research graphs through the Model Context Protocol.

Enables AI agents and MCP clients to run deterministic deep research consensus arbitration by parsing queries, evaluating source authority and contradictions, and returning structured JSON dossiers and telemetry.

Enables autonomous agents to cross-reference factual claims against multiple source documents, detect ungrounded statements, and compute normalized confidence scores. It supports multi-source corroboration and claim verification through a single MCP tool.

Enables autonomous research workflows to construct and analyze multi-source cross-citation graphs and resolve consensus from structured outputs via MCP.

Research methods, workflow tools, and independent review for AI agents, packaged as a Skill, plugin, and local MCP server.

Deep Research for crypto - free & fully local 🧠

Recommends study designs for a research question, states the identifying assumptions to verify, and returns runnable R, Python, or Julia code with a formatted citation for every source, drawn from methodological textbooks, an R package, and research articles on causal inference, econometrics, statistics, and machine learning.

MCP server for evidence-aware video research, providing tools to analyze local videos, inspect specific time windows, and analyze Bilibili videos with provenance tracking and optional audio removal for privacy.

Empowers coding agents for machine learning research by providing access to Lacuna's research map, including novel research proposals, research directions, papers, authors, venues, institutions, and hypotheses. It enables searching and retrieving context-aware research information through MCP tools.

Enables any MCP client to drive a research-to-report workflow end to end: planning a source-target plan with kill criteria, scoring each fetched source with an explainable 0–100 quality breakdown, and assembling a citation-registry report. Report checking mechanically enforces citation coverage, returning orphan claims as an error list rather than a pass.

Exposes fourteen read-only tools over the HEY Research public API, letting assistants look up Robinhood Chain projects, builders, shipped work, relationships and market context, with each answer tagged FACT, DERIVED or UNKNOWN and unmeasured fields omitted rather than zeroed. Runs over stdio or hosted Streamable HTTP, and gives no trade instructions.

Enables Claude Code to run live product searches, compare cross-retailer prices, check Amazon price history, surface community deals, and optionally cross-check finalists via Capital One Shopping, with every tool reporting its checked and skipped sources.

An append-only research operations framework and read-only MCP that tracks research plans, approvals, observations, claims, failures, revisions, and contributions with source-grounded evidence, providing search, evidence fetch, and audit capabilities without direct ledger writes.

Enables read-only, provenance-aware research over Discord by pairing an explicitly authorized Discord Desktop local-RPC/OAuth2 path for bounded live channel snapshots with message, thread, and channel search across a locally maintained archive, without writes, deletes, or session-token automation.

Pay-per-call x402 crypto research and Base address/approval risk checks, capped wallet.

Enables AI assistants to search and read an open quant research record: papers, topics, killed candidates, trial counts, live paper-trading sleeves, and a tamper-evident chain head. It provides six read-only tools over public CDN files, returning each source's stated limits alongside paper-execution-only caveats.

Cross-chain cryptocurrency swaps via Chainflip. Get quotes, execute swaps, and track progress. No API key required to get started.

Enables deterministic auditing of multi-hop agent trajectories through cyclic loop detection, diversity scoring, and execution drift prevention via the Model Context Protocol.

Enables AI clients to search, retrieve, and cite a global investment research knowledge base spanning millions of sell-side reports, company filings, meeting notes, papers, and in-report charts, returning source passages with page numbers for verifiable answers and continuous reading. Supports natural-language queries filtered by institution, industry, or date across Claude, Cursor, Codex, and other MCP clients.

A read-only MCP server for EdgeDepth's market microstructure search engine, enabling users to query recorded crypto and TradFi perpetuals for market conditions, outcomes, and reproducibility-keyed evidence directly from MCP clients.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Enables AI assistants to answer peptide questions from PepBank study summaries with cited sources, and to look up catalog products with variants, prices, stock and per-lot lab reports (COAs). Also covers store policies and generates cart links for checkout on curo.you.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.