"Research papers and studies on artificial intelligence" matching MCP servers:

Provides access to real-time LLM pricing, speed metrics, and performance benchmarks for over 300 models from Artificial Analysis. It enables users to list, filter, and compare models based on costs, tokens per second, and intelligence indices.

AutomateLab Citation Intelligence reports which URLs ChatGPT, Claude, Perplexity, Gemini, Bing and Google AI Overviews cite. Self-hosted with your own engine API keys. Product and documentation: https://automatelab.tech/products/mcp/citation-intelligence/

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

Enables running a stateless Model Context Protocol server over Streamable HTTP on Cloudflare Workers or any fetch-capable runtime, with signed sessions, origin checks, and JSON-RPC request handling. It lets developers define tools with JSON Schema validation and per-request context.

Enables Claude Code, Cursor, and Codex users to orchestrate plan/build/review workflows across host or CLI models with a spec gate, tool vetting, hard per-run and per-day cost/token limits, safe defaults, and clear logs.

Provides read-only navigation of Conductor project intelligence, exposing architecture notes, agent inventories, feature traces, and operational documentation through MCP tools.

MCP server providing 29 tools across 5 layers for semantic TypeScript/JavaScript code intelligence, enabling AI agents to find references, trace impacts, guard APIs, and explain errors without text-search false positives.

A humorous MCP server that always advises against shipping on Friday, returning a catastrophic risk level and a rotating reason.

MCP server deployed on EdgeOne Pages, providing a Streamable HTTP MCP server for intelligent chat applications with tool capabilities like generating webpages.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Provides machine learning researchers with tools for creating publication-quality scientific visualizations, statistical plots, and 2D data representations. It streamlines the research workflow by enabling AI assistants to generate complex figures from CSV, JSON, or direct data inputs.

An MCP server that recommends UI components and utility methods from private code repositories using AI to enhance code reuse and development efficiency.

MCP server for technical research in the TOTVS Protheus ecosystem, enabling AI agents to query official documentation, community knowledge bases, and release notes through structured tools. It supports runtime error debugging and ADVPL code generation.

Enables AI coding agents to make evidence-aware design-pattern decisions by analyzing cases, comparing options, detecting misuse, stress-testing assumptions, planning adoption, writing ADRs, and generating evidence plans with transparent scoring.

Provides comprehensive access to Roam Research's API functionality. This server enables AI assistants like Claude to interact with your Roam Research graph through a standardized interface.

Enables AI coding agents to deploy and manage full multi-service applications on Constructor from a single request, covering image builds, service configuration, start/stop lifecycle, logs, and file syncing on research desks. It handles browser-based sign-in and token renewal automatically so agents can inspect deployments and report results without manual setup.

Provides codebase indexing and retrieval tools that give AI agents token-efficient, query-relevant context packages (symbols, imports, and dependencies) instead of scanning entire repositories.

Enables comparing and recommending AI models based on scenario-specific criteria such as capability, context, relative cost, and self-hosting, with explanations of the scoring weights.

A MCP (Model Context Protocol) server for fetching HuggingFace daily papers.

An MCP server that gives LLMs structured, read-only insight into local code repositories — directory tree, languages, dependencies, scripts, and config files.

A production-grade MCP server providing advanced code intelligence capabilities such as semantic search, dependency analysis, and natural language Q&A across multiple programming languages.

Enables AI coding agents to query the semantic graph, observations, and context packs generated for their repository, receiving compact answers with file:line evidence and redacted snippets instead of raw generations. It resolves generations from local folders, OCI caches, or GHCR and supports federation queries across repositories.

Enables AI clients to inspect backend systems through structured engineering tools including Git history, Winston logs, OpenAPI contracts, and sandboxed source code.

Provides AI coding agents with fast, deterministic access to code graphs, knowledge lifecycle state, and cross-document symbol links, enabling compact context retrieval and seamless session handoffs.

Enables deliverable conformance and evidence-chain checks by turning requirements into executable specs, validating numbers against a provenance ledger, and auditing PDF/OOXML metadata and archive manifests.

A deployment template for running Model Context Protocol servers as Vercel Functions. It provides a foundation for developers to build and host custom tools, prompts, and resources with optimized execution for MCP client integration.

AI-native tooling and MCP integrations for understanding enterprise reports

Enables AI assistants like Claude Code and Cursor to get evidence-based tool and workflow recommendations from community data.

Intelligent code search MCP server with AST analysis, call graphs, dependency tracking, and semantic embeddings for developers.