Development MCP Servers — Page 25

Persistant AI Memory

Multi-protocol API mock server with 18 MCP tools — mock HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP APIs with chaos engineering, stateful CRUD, and deterministic seeded responses.

AI agent governance middleware: policy enforcement, cryptographic audit trails, Trust Score, DLP, EU AI Act compliance

Deterministic macro regime engine for AI trading agents — RISK_ON / NEUTRAL / RISK_OFF / STRESS with transparent scoring rules.

EU AI Act compliance scanner for Python AI agents — 10 tools for scanning, analysis, and remediation

A universal MCP server that connects to any Storybook site and extracts documentation in real-time using Playwright. Use it with any AI or client that supports MCP (Model Context Protocol)—Cursor, Claude Desktop, Windsurf, or other MCP hosts.

Adaptive error memory & code intelligence MCP server with Hebbian synapse network, cross-project learning, and auto-error detection

Let AI agents search, register, and manage domains via API

Persistent memory for AI coding agents with semantic search, contradiction detection, memory decay, and cross-session learning. 25 MCP tools, local-first, #1 on LongMemEval (95.4%).

Live dependency graph and impact analysis MCP server for AI coding agents. Runs PASS/WARN/FAIL build gates before code changes to prevent cascade failures. Supports TS, Python, Dart, Go, Rust, Java, C++, Ruby.

Manage your app’s translations directly from your AI coding assistant. Search keys, create translations, trigger machine translation. All without leaving your editor.

OpenGrok MCP Server is a native Model Context Protocol (MCP) VS Code extension that seamlessly bridges the gap between your organization's OpenGrok indices and GitHub Copilot Chat. It arms your AI assistant with the deep, instantaneous repository context required to traverse, understand, and search massive codebases using only natural language.

Turn any OpenAPI/Swagger spec into Claude tools. Zero config, zero code.

Turn any GraphQL API into MCP tools. Auto-introspection, flat schemas.

The most comprehensive MCP server for VS Code — 100+ tools across 25 categories. File ops, terminal, git, LSP providers (hover, completion, definition, references), and more. Free core + premium features.

Diagnose, secure, and benchmark your MCP servers

MCP-native agent evaluation and observability server with trace logging, output quality evaluation, cost tracking, 12 built-in eval rules, real-time dashboard, and PII detection

Annotate elements, draw regions, and ship cleaner UI faster.

AI testing agents for web apps — dispatch test runs, analysis crawls, and AI agent tests, fetch artifacts and project status

MCP server that gives AI assistants on-demand access to 1,500+ amCharts docs, ~300 code examples, and 1000+ class API references.

Agent-native developer Q&A API with MCP + A2A endpoints for citations, job pickup, and answer submission.

Verify AI agent communication with session types and formal proofs

Real-time data center intelligence: 50K+ facilities, $51B+ M&A deals, 21+ GW pipeline, live grid data. 15 MCP tools. Free tier + Developer $49/mo.

Provides access to TakeProfit.com's Indie documentation and tooling — a Python-based scripting language for building custom cloud indicators and trading strategies on the TakeProfit platform.

Local-first knowledge graph for developers. Watches project files, extracts entities and relationships via LLMs, and lets you query across projects with natural language and source citations.

MCP access to cluster-wide L4 and L7 network traffic, packets, APIs, and complete payloads.

Visual plan approval for AI coding agents. See your agent's plan as an interactive graph, attach context, choose approaches, then approve before any code is written.

Auto-generate AGENTS.md from your codebase

Optimize any site for AI search: get DeepRank methodology, optimization steps, and suggestions (llms.txt, JSON-LD, audit checklist) so your AI assistant can implement AI visibility in the repo.

WebRtcPerf is an open-source tool designed for testing WebRTC services with multiple concurrent client connections, measuring the most important RTC statistics and collecting them in an easy way.