"An introduction to OSINT (Open Source Intelligence)" matching MCP servers:

Fill standard legal agreement templates (NDAs, SAFEs, NVCA docs, employment, cloud terms) and produce DOCX files.

An MCP server that enables AI assistants to navigate, search, and analyze local Keycloak source code to support developer customizations like SPIs and authenticators. It provides tools for searching classes, generating boilerplate code, detecting breaking changes between versions, and tracing dependencies.

Local-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs

Open Kioku is the local-first code intelligence and evidence layer for AI coding agents (Claude, Cursor, Codex, Zed, and other MCP clients). Instead of letting agents blindly crawl files, guess blast radius, or read the entire repository repeatedly, Open Kioku gives them a precise, pre-indexed code index to build evidence-backed plans before they edit, and verify boundary limits after they edit.

Provides on-demand access to AOSP and Jetpack source code to help AI understand Android framework internals. It features a hybrid architecture using Tree-sitter and LSP for precise code extraction, cross-file navigation, and local source indexing.

Analyzes source code dependencies across multiple programming languages in the specified directory to identify file relationships, assisting in dependency management and project structure understanding.

An MCP server providing stock market data and trading capabilities through multiple broker APIs including Robinhood and Schwab.

An open-source Model Context Protocol application management platform that allows users to create applications from GitHub repositories with automatic information extraction and database integration.

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

MCP server that builds a deterministic, source-traceable knowledge index of any codebase, enabling glossary lookup, code graphs, and exact-token search with every fact linked to its source file and line.

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.

Indexes Unreal Engine source code into a local database, providing AI coding assistants with deep structural queries like class hierarchies, call graphs, and full-text search across all engine source files.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A private, open-source AI-text checker. Get a read on whether text looks AI-written, the exact AI-tell spans to fix, a reuse check, and a grammar pass.

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

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.

A local MCP server that delegates tasks to a subagent runtime via OpenAI-compatible interfaces, enabling file operations, command execution, and rollback of local file changes.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.