"Python Code for Data Analysis" matching MCP servers:

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

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

Enables LLMs to interact with embedded devices by reading and writing Segger RTT data through a J-Link debugger.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

A persistent, Git-versioned map of your whole codebase and database schema that coding agents read before they touch anything. Local-first MCP server + CLI in Go: a governed repository index of code knowledge that gives Claude Code, Codex, Cursor, and opencode long-term context, memory, and code intelligence.

Enables AI coding agents to query a semantic cross-repository code graph for symbols, references, callers, dependencies, and change impact across registered repositories.

Connect Legacy Databases to AI Agents via Model Context Protocol. Open-source bridge for LLM data analysis.

Local-first code intelligence for AI coding assistants: MCP tools, symbol graph search, impact analysis, and auto-index watch for Cursor, Claude Code, and Codex.

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.

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.

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

Code-pinned team memory for AI coding agents — typed artifacts (Decision/Analysis/Debug/Task), MCP-native workflow, self-host with Docker Compose.

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

Connects AI tools to GitHub and local git repositories, enabling natural language management of issues, PRs, code analysis, and workflows.

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

Persistent project memory and task management for AI coding agents through MCP. Lets Claude Code, Cursor, Codex and other MCP clients save decisions and bug fixes, search relevant context, and reuse it across sessions.

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.

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

Enables local, read-only analysis of Codex and Claude Code conversations through ten MCP tools for browsing sessions, inspecting tokens and tools, and comparing sessions without accounts or cloud services.

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