"A server that supports Server-Sent Events (SSE)" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Enables executing arbitrary Joern/CPGQL queries against a loaded Code Property Graph, loading source code in multiple languages (PHP, Java, JavaScript, Python, C/C++) to build new CPGs, and inspecting loaded projects and the active workspace. It communicates with a running Joern server over its synchronous HTTP query endpoint, so no state polling is required.

Zero-dependency MCP server inspector for protocol conformance, tool annotations, and capability checks.

Lets AI agents ask which tests a Playwright or Vitest project contains, which are skipped and why, by reading the test source files statically. Nothing is executed, written, or sent over the network, and answers come back as paged JSON with summaries, filters, and scan diagnostics.

Enables scanning diffs or code blobs for leaked secrets, returning a verdict with severity and masked findings, all processed locally with no data sent externally.

The MCP server for Nanostores that scans your codebase with AST analysis to find stores, subscribers, and dependency chains, and can ingest live events to spot noisy, error-prone, or unused stores.

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An MCP server that scans React and Vue projects, extracts component metadata (props, slots, events, imports, usage), and exposes it to AI coding agents via structured tools.

An AI-native code security audit MCP server that supports multi-language AST analysis, call graph analysis, vulnerability detection, and AI deep audit.

Enables AI to precisely use local Vue components by extracting their Props, Events, and Slots via AST analysis.

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

Enables AI-driven reverse engineering with x64dbg via 71+ MCP tools for breakpoints, memory, disassembly, tracing, debug control, PE analysis, and anti-anti-debugging, supporting HTTP, SSE, and stdio transports.

Send requests to OpenAI, MistralAI, Anthropic, xAI, or Google AI using MCP protocol via tool or predefined prompts. Vendor API key required. Both STDIO and SSE transport mechanisms are supported via arguments.

An MCP server that analyzes GitHub repositories and automatically generates README.md files. Supports multiple AI providers and offers web, MCP tool, and n8n workflow modes.

Enables AI coding agents to query a pre-built semantic knowledge graph of code, reducing token usage and tool calls. Supports 16 tools for code exploration, analysis, and context building.

Enables LLMs to perform JVM bytecode analysis and editing by operating a Recaf workspace through MCP tools. Supports class browsing, decompilation, bytecode manipulation, search, cross-references, and refactoring operations.

A headless Ghidra server that enables AI agents to perform deep reverse-engineering tasks such as disassembly, decompilation, and patching via the Model Context Protocol. It supports extensive automation of analysis workflows in sandboxed environments through a catalog of over 200 specialized tools.

Enables AI coding agents to retrieve precise, real-time architectural context—such as domains, models, routes, and events—from a codebase, avoiding the need to dump entire files into prompts.