Los mejores MCP servers de Developer Tools para Codex

Provides a local knowledge graph that connects source code, documentation, and infrastructure to give AI agents structural context.

[mcp_servers.codebase-memory-mcp]
command = "npx"
args = ["-y", "codebase-memory-mcp"]

Securely execute LLM-generated code in isolated containers or local Linux and Windows sandboxes across multiple programming languages.

[mcp_servers.llm-sandbox]
command = "uvx"
args = ["llm-sandbox"]

Lets an AI client create, inspect, validate, and save editable 3D building scenes, including walls, rooms, doors, and furnishings.

[mcp_servers.editor]
command = "npx"
args = ["-y", "@pascal-app/mcp"]

Lets AI agents search, run, and read results from thousands of web scraping and automation Actors on Apify Store.

[mcp_servers.apify-mcp-server]
url = "https://mcp.apify.com/"

Provides AST-based semantic code search for local repositories using incremental re-indexing and natural language queries.

[mcp_servers.cocoindex-code]
command = "uvx"
args = ["cocoindex-code"]

Lets an AI client read and change Google Ads, Reddit Ads and GA4 campaigns, with a preview shown before every change.

[mcp_servers.adloop]
command = "uvx"
args = ["adloop"]

An agent meta-harness that provides Claude Code and Codex with specialized agent swarms, self-learning memory, and enterprise security guardrails.

[mcp_servers.claude-flow]
command = "npx"
args = ["-y", "claude-flow"]

Enables LLMs to interact with web pages through structured accessibility snapshots using Playwright browser automation.

[mcp_servers.playwright-mcp]
command = "npx"
args = ["-y", "@playwright/mcp"]

Allows an AI client to interact with Bitbucket Data Center repositories and code through the Model Context Protocol.

[mcp_servers.atlassian-dc-mcp]
command = "npx"
args = ["-y", "@atlassian-dc-mcp/bitbucket"]

Lets an AI agent draw and edit draw.io diagrams on a live browser canvas that you can also edit by hand.

[mcp_servers.next-ai-drawio]
command = "npx"
args = ["-y", "@next-ai-drawio/mcp-server"]

Packs a local or remote codebase into a single AI-friendly file with token counts so LLMs and coding agents can read or search it.

[mcp_servers.repomix]
command = "npx"
args = ["-y", "repomix"]

Connects AI agents and IDEs to enterprise databases using prebuilt tools or a custom framework for secure, structured queries.

[mcp_servers.mcp-toolbox]
command = "docker"
args = ["run", "-i", "--rm", "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:1.17.0"]

Connects AI agents and IDEs to enterprise databases using prebuilt tools or a custom framework for secure, structured queries.

[mcp_servers.genai-toolbox]
command = "docker"
args = ["run", "-i", "--rm", "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0"]

Helps developers add authenticated MCP support to clients and servers with metadata, auth handlers, and feedback tools.

[mcp_servers.mcp-tools]
command = "npx"
args = ["-y", "@clerk/mcp-tools"]

Reverse engineer binaries, applications, and runtime behavior through an AI agent or terminal interface.

[mcp_servers.rea]
command = "npx"
args = ["-y", "rea-agents"]

Lets an AI client fetch web pages with stealth HTTP or real browsers, bypass Cloudflare, and extract data using CSS selectors.

[mcp_servers.scrapling]
command = "uvx"
args = ["scrapling"]

Fetches up-to-date, version-specific library documentation and code examples into an AI coding agent's context.

[mcp_servers.context7]
command = "npx"
args = ["-y", "@upstash/context7-mcp"]

Allows AI agents to query over 100 different databases using pre-configured connections.

[mcp_servers.dbx]
command = "npx"
args = ["-y", "@dbx-app/mcp-server"]

Lets AI clients search n8n nodes, templates and docs, validate configurations, and build or deploy n8n workflows.

[mcp_servers.n8n-mcp]
command = "npx"
args = ["-y", "n8n-mcp"]

Enables AI clients to write, backtest, and analyze quantitative trading strategies using a high-performance Rust-based engine.

[mcp_servers.akquant]
command = "uvx"
args = ["akquant"]