"A Dockerized Python Code Execution Environment" matching MCP servers:

An MCP server to create secure code sandbox environment for executing code within Docker containers.

MCP server that provides AI coding assistants with access to call graphs, data flows, and security analysis for multi-file vulnerability detection.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.

An MCP server for fast local source code searching using Zoekt, enabling regex and substring queries across indexed directories.

Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.

AI modifies a function but misses 5 callers that also need updating. crag fixes this — it builds precise call graphs via static analysis, so AI knows exactly what's affected before making changes.

RegressGuard is an MCP server that records a known-good baseline and lets AI coding agents detect regressions (broken API contracts, failing tests, schema changes) during their edit loop, allowing them to self-correct before committing.

An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.

A TypeScript server implementing the Model Context Protocol that provides secure code execution in isolated Docker containers, allowing LLM applications to safely run Python, Go, or JavaScript code snippets.

Open-source MCP and LLM gateway that aggregates MCP tools behind a unified endpoint with governance, observability, and explicit execution controls.

Execute code in 8 programming languages via gVisor-sandboxed Docker containers. Supports Python, JS, TS, Go, Java, C++, C, and Bash.

Seamlessly bring real-time production context—logs, metrics, and traces—into your local environment to auto-fix code faster.

Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.

MCP server that executes caller-supplied Python code in a network-isolated, locked-down sandbox and returns stdout/stderr/exit code. Supports stdio, HTTP, and SSE transports with optional auth.

MCP server for Lightpanda headless browser enabling ultra-fast HTML extraction, markdown conversion, and JavaScript execution with 16x lower memory footprint than Chrome.

Governed execution cells for AI agents via MCP; provides shell, code, file, and browser tools inside isolated, policy-enforced Citadels with deny-by-default security, human-in-the-loop approvals, and tamper-evident audit trails.

High-performance code graph and code intelligence engine. Index code base into knowledge graph, supports 257 languages and native multi repositories environment

what is go-mcp-postgres? go-mcp-postgres is a Model Context Protocol (MCP) server designed for interacting with Postgres databases, allowing for easy CRUD operations and automation without the need for a Node.js or Python environment.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.