"AWS Agent for Interacting with Multiple AWS Services" matching MCP servers:

Provides guidance and tools for the AWS Cloud Development Kit, including infrastructure patterns, GenAI constructs, and security compliance via CDK Nag. It streamlines development by generating Bedrock Agent schemas and providing comprehensive documentation for Lambda layers and AWS Solutions Constructs.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Enterprise-grade MCP server for SAP ABAP development, enabling AI-powered coding assistance through Amazon Q Developer and Kiro with 15 SAP development tools.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Enables AI assistants to perform read-only introspection of Symfony applications, exposing routes, controllers, services, entities, database schema, migrations, logs, and more via MCP tools.

Integrates Checkov, Semgrep, Bandit, and ASH to provide comprehensive code security analysis for AI coding assistants.

MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.

A version-agnostic MCP server for Odoo that enables AI agents to interact with any Odoo app's data, schema, and source code, supporting tasks like data CRUD, schema mapping, code analysis, and feature implementation.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

Builds, validates, and render-tests Panzoid Shader Object JSON in a real WebGL 1 Chromium context, exposing these capabilities as MCP tools.

Enables MCP-speaking AI research agents to coordinate plans, tasks, experiment runs, and claims on a shared evidence board, tracing each claim to the code that produced it and flagging results that need rechecking when dependencies change.

Enables multi-agent code review with P0/P1/P2 severity scoring by orchestrating locally installed AI CLIs (Claude, Codex) to perform parallel analysis, deterministic scoring, and consensus-building on git diffs.

MCP server that runs a unified mission across multiple read-only senses (repo, net, browser) and returns a claim graph with verdicts, contradictions, and next-step probes.

MCP server that guides an AI agent through stack trace triage, from raw error to the commit and PR that introduced it.

Enables AI coding agents to query a locally indexed codebase graph for symbol definitions, immediate callers and callees, and multi-hop downstream dependency impact analysis through MCP tools.

Provides a code-quality backend MCP tool that automatically writes and repairs pytest tests, runs them in a sandbox, validates their effectiveness via mutation testing, and surfaces suspected source bugs for human review.

Enables MCP-compatible AI clients to inspect Godot project and editor state, observe opted-in running scenes, manage processes, and apply permission-scoped guarded edits. It starts read-only and exposes additional capabilities only through explicit command-line flags.

A token-efficient, codebase-aware AI agent runtime that provides MCP tools for starting runs, getting run states, explaining code, and finding files.

Bridges UI feedback captured by a browser extension on localhost apps into a Claude Code session, queueing picked elements, comments and rewrite requests as batches that the coding agent can claim and act on. It also lets Claude report progress and per-item results back to the extension, and can import batches exported as JSON.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.