"Understanding Server-Sent Events (SSE)" matching MCP servers:

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

Enables agents to analyze codebases (local or GitHub) and automatically generate Mermaid diagrams rendered as PNG images via Kroki, providing visual understanding of project structure and flow through file discovery, reading, and diagram generation.

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.

Enables AI agents to analyze and search IFS Cloud codebases using hybrid semantic-lexical search, PageRank importance ranking, and dependency graph analysis. It supports comprehensive exploration of PL/SQL, entities, and projection files to facilitate intelligent architectural understanding.

A Model Context Protocol server for local repository indexing and code understanding, enabling semantic search, AST analysis, dependency tracking, and symbol resolution.

Exposes local Ollama as an MCP server so Claude can delegate drafting, summarization, translation, code review, error explanation, model listing, health checks, and file reading to local models via stdio or HTTP.

Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.

An MCP server that enables users to compile C++ code and retrieve assembly output through the Compiler Explorer (godbolt.org) API. It supports standard tool calls and Server-Sent Events for streaming compilation status and results.

Enables dependency, security, and coding convention checks for Python and Java projects via MCP tools. Supports local paths or Git URLs.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

MCP server for AI-assisted development on the Lampa open-source TV app, providing read-only access to the source tree with 41 tools and 5 resources for structured analysis, planning, editing, and validation.

Enables AI coding agents to list, read, create, update, delete, and render PlantUML and Mermaid diagrams, and check them against the actual codebase to detect architecture drift.

Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

Enables read-only access to the canonical-vault GitHub repository through MCP, letting clients list files, retrieve file contents and history, inspect commits, and search code.

Scans diffs, files, and snippets for leaked secrets like AWS keys, GitHub tokens, and private keys, returning redacted findings while running fully locally without network calls.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

Enables AI agents to search Minecraft obfuscated name mappings (class, method, field) across 38 versions, aiding modding, plugin development, and reflection.

Enables AI agents to explain regex patterns in plain English and statically assess ReDoS risk before shipping, without executing the pattern or requiring an API key.

Verify AI agent communication with session types and formal proofs. 4 tools: parse protocols, verify messages, check safety properties, browse 20 stdlib templates.

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.