"Information on Conducting In-Depth Research Techniques" matching MCP servers:

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables evidence-grounded implementation research by searching GitHub, scoring candidate repositories, extracting source evidence, and generating planning artifacts like research and implementation checklists.

A stdio MCP server that queries Commonware blockchain research via NotebookLM, enabling users to ask research questions, get code-backed implementation suggestions, search reference repositories, and validate documents against source code.

MCP server for ai-scanner that enables AI agents to scan codebases for LLM usage, AI frameworks, and exposed secrets.

Enables MCP clients to drive the complete mobile security toolkit—static/dynamic analysis, Frida hooks, runtime exploration, traffic interception, network setup, and IoT scans—through engine-exposed tools.

Get your research artifact ready for Artifact Evaluation before the deadline: scan the repo, scaffold the easy fixes, verify the run path, and generate the appendix.

MCP server that provides npm package information for AI agents during TypeScript development.

Architectural sensor for Python codebases. Scores structural health (modularity, acyclicity, depth, equality), detects import cycles, enforces YAML layer rules, and runs a snapshot/diff loop so AI-assisted edits do not silently regress structure.

Enables AI assistants to understand Unity games and build mods by querying and acting on a combined knowledge base built from static analysis, online research, and an in-game runtime agent, with user consent required for any changes.

An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.

Enables local detection of protected health information in source code before it reaches LLM prompts, log statements, or analytics calls.

An MCP server for the OpenAI Codex CLI that provides coding assistance with multi-turn session management and reasoning depth control. It enables users to perform code analysis, generation, and refactoring through Claude with native resume support for conversational context.

A code review tool server based on Model Context Protocol (MCP), providing multi-dimensional code review and scoring functions.

Lien connects AI coding assistants like Cursor and Claude Code to your codebase through the Model Context Protocol (MCP). Ask questions in natural language, get precise answers from semantic search—all running locally on your machine.

MCP server for fetching GitHub repository files and directory trees, supporting raw file content, unix-style directory trees, and enhanced trees with file sizes, depth limits, and filters.

Model Context Protocol server for security research automation, integrating multiple security testing tools into LLM-driven workflows for secret scanning, static analysis, and vulnerability discovery.

Compiler-in-the-loop steering for coding agents - Cursor and Claude Code. It runs your workspace's real language server on each edit, extracts diagnostics scoped to the changed lines and type signatures, and feeds that back to the coding agent.

Enables AI coding agents to inspect Runable projects over MCP, providing read-only access to project information and configuration via Runable's inspector.

Provides MCP tools to check a package's maintenance status, licence, and security advisories before you depend on it, with per-call payment in USDC on Base mainnet via x402.

Provides MCP tools for AI-powered code review, research, and book writing via a fleet of coding agents.