"MCP servers with streamable-http support" matching MCP servers:

Enables AI assistants to work with Chapel code, including compiling, linting, and accessing educational primers.

Enables AI assistants to explore, search, and read codebase repositories and API specifications efficiently, with support for file searching, content search via ripgrep, and reading API specs.

An HTTP-based MCP server that provides filesystem tools and code analysis, enabling LLMs to read, write, list files, and analyze code securely.

A collection of MCP servers providing structured tools for ARM specification, verification, assembly analysis, and performance checks. They enable LLM agents and engineers to perform formal verification, analyze assembly code, and evaluate performance constraints.

Exposes the sigmap MCP server (code analysis tools) over Streamable HTTP via supergateway, allowing remote MCP clients to query code context, signatures, and more.

Enables structured, iterative reasoning for complex problem-solving with features like confidence tracking, revision mechanisms, and branching support. Provides flexible validation and multiple output formats for systematic analysis and decision-making tasks.

40 regulation-and-deadline linters (CRA/CSAF, PCI DSS 6.4.3, WCAG 2.1 AA, DORA, NIS2, EU AI Act, KSeF, NF-e) that AI agents call over MCP. Free checks on the open file; licence key unlocks workspace scan and CI exit code.

Exposes Cursor IDE's MCP tools (codebase search, file operations) as an HTTP API for integration with Open WebUI, n8n, and other automation tools.

Provides code generation and completion capabilities using the DeepSeek API, with support for tool chaining and cost optimization.

Integrates local language models (like Qwen3-8B) with MCP clients, providing tools for chat, code analysis, text generation, translation, and content summarization using your own hardware.

MCP server exposing GitHub tools for issues, pull requests, and code browsing via the GitHub REST API. Designed for local LLM clients with flat arguments and streamable HTTP support.

Enables ChatGPT Pro web to securely read workspace files, git diffs, and test records through OAuth-protected read-only MCP tools, so it can plan and review while Codex handles execution without uploading the repository.

Enables interactive GitHub pull-request review from Claude Code, with tools to fetch PRs, inspect files and repo structure, post review comments, and query a RAG index of the codebase.

Provides a code search service via MCP, allowing AI clients to perform fast, indexed searches across large codebases using Zoekt, with support for filters like repository, language, and path.

Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.

Enumerates everything in a code checkout addressed to an AI agent, including instruction files, hook commands, declared MCP servers, and skills/subagents, so you can review what your agent will actually follow.

14 atomic MCP tools for AppSec and AI Security engineers: source/schema/prompt audit primitives, JWT inspect, HTTP diff, pentest atoms (default creds, GraphQL introspect, phpggc, interactsh OOB), and a defensive helpers library that fixes the bugs the detectors flag. SARIF output, PyPI Trusted Publishing with Sigstore provenance.

Audits local package folders to generate publish-readiness reports and previews of NPM tarball contents. It helps developers identify and resolve configuration issues like missing types or broken exports before releasing code.

A stdio MCP server that audits other MCP servers by linting their tool schemas and calling tools with malformed inputs to produce a 0–100 conformance score and Markdown report.

An intelligent debugging assistant that automates the debugging process by analyzing bugs, injecting HTTP-based debug logs into code across multiple environments (browser, Node.js, mobile, etc.), and iteratively fixing issues based on real-time feedback.