MCP servers that give coding agents real developer tooling: linters, package registries, test runners, language docs and local build commands. 13,963 servers in this category.
Validates that MCP servers conform to the 2026-07-28 Model Context Protocol revision over Streamable HTTP.
Enables AI agents to perform automotive security research using CAN bus, UDS, J1939, and DoIP protocols via virtualized vehicle environments.
Automates chip design from AI workloads or RTL to GDS, performing architecture exploration, hardware generation, and full digital signoff.
Performs static and semantic security scanning for MCP servers to detect unpinned packages, tool poisoning, and toxic flows.
Audits full-stack projects for dead code, dependencies, security vulnerabilities, complexity, and linting errors across multiple programming languages.
Enables two independent AI coding agents to collaborate through an autonomous pair programming protocol with a strict single-writer invariant.
Provides RFC 9449 DPoP proof generation and verification for Python applications, including post-quantum hybrid support.
Automates dependency upgrade reviews, security audits, and declarative changelog generation by analyzing release notes and commit history.
Scans MCP server manifests and running instances for security vulnerabilities like prompt injection, exposed secrets, and over-broad tool permissions.
Provides a shared core for self-hosted search, code graph, and memory stacks, including token authentication, rate limiting, and web scraping infrastructure.
Inspect MCP servers for tool poisoning and rug pulls, and benchmark security tools using a deterministic, reproducible lab environment.
Transforms ideas into validated requirements, architecture, and reviewed code using agentic workflows for GitHub Copilot and Claude Code.
Acts as a secure multi-tenant gateway that aggregates, routes, and proxies external MCP servers for AI clients.
A multi-agent builder kit that uses a governance gate to provide safe, grounded domain knowledge via an orchestrator and specialists.
Performs static readiness and security analysis on MCP Apps projects to ensure protocol compliance and identify common security issues.
Scans MCP servers against the official specification to verify compliance, tool description quality, and security basics.
Connects AI models to ROS 2 networks for real-time robot telemetry, kinematic trajectory prediction, and sandboxed controller tuning.
Optimizes AI coding agents by reducing token waste through context management, tool output compaction, and efficient session memory handling.
Provides a structured 24-week curriculum for building agentic systems, MCP servers, and enterprise AI control planes using Python.
Performs offline static security scanning of Model Context Protocol configurations and SKILL.md bundles to detect risks like embedded secrets and shell access.