MCP servers that give coding agents real developer tooling: linters, package registries, test runners, language docs and local build commands. 13,971 servers in this category.
Provides a read-only interface for AI assistants to perform Linux system diagnostics including process monitoring, disk usage, and log inspection.
Filters and retrieves relevant MCP tools for AI agents based on user permissions and hybrid search to reduce latency and prevent unauthorized tool exposure.
Provides a curated directory of verified MCP servers optimized for running on Android devices via Termux or PRoot.
Provides deterministic data-validation tools including contract validation, arithmetic reconciliation, entity counting, and duplicate detection for AI clients.
Discover, inspect, and install verified MCP servers into Claude Desktop, Cursor, and mcp-mesh via a command-line interface.
Lets an AI client read, search, and inspect code repositories through 18 safe tools with mandatory human approval for any file changes or test runs.
Lets an AI agent query Bitcoin and Stacks blockchain data, including balances, transaction history, and plain-English transaction explanations.
Checks MCP server tool names against reserved framework names to prevent tool shadowing and dispatch errors.
Probes MCP server releases to detect schema drift and tool definition loss caused by dependency resolution issues.
Allows tenant administrators to manage shared drives, permissions, and user account states via service-account delegation.
Provides a persistent, inspectable IPython environment that allows AI agents to maintain state and variables across multiple code execution cells.
Lets an AI client develop Fabric notebooks, Dataflow Gen2, and manage Lakehouse/Warehouse data via the Fabric REST API.
Provides wire-level observability, behavioral detection, and enforcement for MCP servers through passive tapping and static auditing.
Analyzes SAP SuccessFactors EC configuration metadata to detect technical debt and generate remediation roadmaps via AI agents.
Allows AI agents to author, render, and critique Pokémon Gen 3 decompilation maps by reading and writing Porymap-compatible files.
Lets an AI agent query live Earth Observation catalogues and perform geospatial analysis using natural language without client-side processing.
Allows an AI assistant to read .sim files and solver logs, search local documentation, and run checked Java macros on active simulation sessions.
Synchronizes context, git worktrees, and session state across multiple AI coding agents like Claude, Antigravity, and Codex on macOS.
Imports, syncs, and indexes Google AI chat history from Gemini, AI Studio, and NotebookLM into a local searchable SQLite database.
Identify active network listeners and safely terminate processes occupying specific ports across Windows, macOS, and Linux.
