"Roam Research" matching MCP servers:

Enables fully local semantic search over a Roam Research graph via MCP, providing tools for hybrid retrieval, index refresh, and stats while keeping all content on-machine.

Enables coding and research agents to run paid, cited deep research on AI infrastructure, MCP, and security topics via remote MCP tools, with query-tied excerpt packs and uncited or failed calls billed at $0.

Enables AI agents to semantically search, retrieve, and augment an org-roam knowledge graph via MCP, with features like vector-based search, YouTube ingestion, and local LLM processing.

Enables federated multi-source research by fanning out queries across web, community, and social sources, deduplicating and interleaving results, and storing a persistent corpus for cross-checking.

Enables semantic search across personal PDF paper collections with page-level citations, allowing users to query their library from any MCP-capable client.

An MCP server for Perplexity's Agent API, enabling multi-step web research with citations through tools to start, collect, and cancel research runs.

Enables AI coding agents to run Tavily-powered web searches and asynchronous, cited research through MCP, with tools for focused search, task creation, and status retrieval.

Generates, validates, and updates structured research tables by synthesizing multiple AI queries, enabling AI agents to autonomously drive research workflows.

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.

MCP server that acts as a research intelligence agent, converting natural language queries into SQL or full-text search against Hacker News and arXiv data, and returning answers with supporting evidence.

Enables AI assistants to perform comprehensive research by searching Google, mining Reddit discussions, scraping web content with JS rendering, and synthesizing findings with citations into structured context.

MCP server that fetches web pages and uses local Qwen models to answer questions about their content, with site-scoped search and map-reduce chunking for long pages.

Shared research cache for AI agents. Caches web research across sessions and users - hit means instant answer from verified sources, miss means your research saves the next dev's tokens. Semantic search with freshness tracking, gap detection, and real-time token measurement via JSONL. Free, open source.

An MCP server that enables saving, retrieving, and managing research content using ChromaDB vector storage and semantic search.

A Python-based agent that integrates research providers (OpenAI, Gemini, DR-Tulu, Open Deep Research) with Claude Code via the Model Context Protocol for automated deep research.

Integrates Perplexity AI's search and research capabilities into Claude Code, enabling web-grounded answers, deep research, code review, and more with real-time citations.

A deep-research MCP server exposing a single task-augmented tool that runs GPT-Researcher with Tavily search, Anthropic Claude, and OpenAI embeddings, streaming progress via MCP tasks and Upjack entity stream.

Enables users to create and refine a research outline, queue report generation in the background, and retrieve progress or completed Markdown reports, with automatic checkpointing so unfinished work can resume after a restart.

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.

Enables comprehensive Reddit research through a three-layer architecture that discovers relevant communities, provides operation guidance, and executes multi-subreddit content fetching with proper citations. Supports searching, post fetching, comment analysis, and batch operations across multiple subreddits for thorough content analysis.