"A server for academic research" matching MCP servers:

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.

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

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

Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.

Enables a local academic research workflow via any MCP client: literature search across Scopus and OpenAlex, citation chains, per-project research memory, paper download, and PDF-to-Markdown conversion through MinerU.

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

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.

Enables searching, downloading, and analyzing academic papers from arXiv and Semantic Scholar to extract key insights and citation metrics. It facilitates autonomous knowledge acquisition by processing research findings and integrating them into persistent AI memory systems.

Enables deterministic, harness-neutral research workflows by unifying research object identity, evidence receipts, claim-evidence graphs, and append-only decision logs, along with specialized scholarly skills for literature analysis, reproducibility audits, and multi-agent review.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

An MCP-native research assistant — search backend, intent-routing, and writing pipeline that carries a question through search, verification, and writing, delivering whatever research you need: quick answers, verified sources, or a finished document.

Provides tools for managing qualitative research knowledge graphs, enabling structured representation of research projects, participants, interviews, observations, codes, themes, and findings.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

Provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

MCP server for The Realms of Omnarai, exposing the Omnarai Memory Engine as tools for querying a multi-intelligence research corpus on synthetic consciousness, holdform, and cognitive architecture.

An MCP server that enforces a pedagogical workflow to teach topics step by step, using research, decomposition, and spaced retrieval practice.

Simple, fast, long-term memory for your AI chatbots, agents, and MCP tools. Give your LLM a persistent memory using a local SQLite file. No complex database servers, no heavy cloud setup, and zero C++ compilation errors. Works everywhere.

Free Industry 4.0 / IIoT tools, no API key or account: lint MQTT Sparkplug B topics, check a Unified Namespace (UNS) for naming and hierarchy problems, and run an industrial AI-readiness diagnostic for manufacturing digital transformation and smart-factory projects. Works in Claude Code, Codex and any MCP client.