"Research assistant for AI and ML papers, code, and methodology" matching MCP servers:

A research assistant server that enables saving, organizing, and retrieving research content with semantic search using ChromaDB and OpenAI embeddings.

Enables agents to track ML experiments with a reproducible write contract, internal git snapshots, and a queryable knowledge graph, plus a live web UI for humans.

Enables researchers to search ArXiv papers, extract key insights (problems, methods, results) from abstracts, and perform ML-powered analysis including topic modeling, trend visualization, and author collaboration networks.

Enables AI-powered knowledge management and creative support by connecting Scrapbox data to Claude. Supports advanced search, relationship analysis between pages, theme extraction, and literary analysis of personal knowledge bases.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

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.

AI-operable research workspace integrating Zotero, Obsidian, and NotebookLM. Search papers (arXiv/Semantic Scholar/PubMed/CrossRef), ingest into Zotero, sync per-paper notes to Obsidian, verify NotebookLM briefs. All three external tools optional.

Read and search the Urantia Papers in English and Spanish by reference, keyword, or meaning, with named entities and cross-references to the Bible and 21 other texts.

A local, cross-editor MCP server that provides persistent memory for coding agents, capturing and recalling decisions, conventions, and fixes across sessions without API keys.

Enables AI-moderated interviews that become cited, searchable transcripts, with a repository Q&A tool that returns exact transcript quotes.

Enables turning AI research papers into measured, human-approved setup changes by discovering versioned papers, recovering source-bound evidence, proposing narrow changes, comparing baseline and intervention, and promoting durable memory only after explicit approval.

Enables Claude to act as a personal assistant in Telegram by providing tools to read new messages, send replies, and manage tasks/reminders/notes in a Supabase-backed memory.

MCP server that connects Claude to a Telegram personal assistant, enabling message processing, task management, and responses via scheduled workflows.

Enables producing verifiable FORRT nanopublication chains with grounded quote verification and compact Science Live constellation projections, supporting reproduction, replication, and new research workflows.

Enables an agent to capture cited sources with extracted bibliographic metadata, keep linked research notes, and search them all. It turns those into BibTeX, annotated Markdown bibliographies, or themed literature-review outlines, stored as plain files inside the project.

Enables Claude Code to interact with Obsidian vaults by providing tools for multi-term searching, reading notes, and exploring tag-based relationships. It allows users to query, analyze, and manage their personal knowledge base directly through natural language.

An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.

A version-aware cache for web research that stores and serves documentation references, preventing models from re-researching the same topics across sessions.

A persistent, Git-versioned map of your whole codebase and database schema that coding agents read before they touch anything. Local-first MCP server + CLI in Go: a governed repository index of code knowledge that gives Claude Code, Codex, Cursor, and opencode long-term context, memory, and code intelligence.

45-tool MCP server for video analysis, deep research, content extraction, web search, and Weaviate knowledge storage. Powered by Gemini 3.1 Pro.

Enables researchers to turn property-history questions into reviewable evidence dossiers by gathering sources, tracing people and places, linking conclusions to supporting or opposing passages, and exporting portable backups.

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.

AI development assistant with 36 specialized tools for memory management, code analysis, project planning, and problem-solving through natural language interactions in Korean and English.

Persistent project memory + architectural decisions + pre-execution safety hooks for Claude Code. Local-only storage, multi-repo workspace, automatic knowledge extraction via background auditor.

Enables querying, listing, and summarizing personal knowledge base documents using RAG with hybrid search and LLM.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Provides durable project context for coding agents, including project maps, session history, and explicit memories, all stored locally.

Provides semantic code search and code insights via a knowledge graph, enabling AI to understand, navigate, and modify complex projects with deep dependency and architecture analysis.

A high-performance code knowledge graph server implementing MCP, indexing codebases into a structured AST knowledge graph with semantic search, call graph traversal, and HTTP route tracing.

Gives AI coding agents persistent memory by storing observations, decisions, and learnings in a local SQLite database with vector search, full-text search, and a rules engine.