"Informational MCP Servers with Croissant Dataset Format Support" matching MCP servers:

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

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.

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.

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.

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.

A token-efficient, schema-aware MCP server that enables AI assistants to safely read, modify, query, and validate JSON, YAML, and TOML files with automatic schema detection and format conversion capabilities.

Structured .aide spec files that give AI agents progressive disclosure into your codebase architecture via MCP.

Enables AI assistants to compile AdvPL/TLPP sources, generate and apply patches, and inspect RPO of TOTVS Protheus servers via the TDS Language Server.

Enables building MCP servers in TypeScript where tool schemas, descriptions, and validation are automatically generated from class methods, their TypeScript types, and JSDoc comments at compile time.

Validates and tests llguidance grammars (Lark format), providing grammar validation, batch test execution, and syntax documentation.

Automatically converts JoinQuant quantitative trading strategies to Ptrade platform format, supporting direct code input or file paths, with automatic API mapping and detailed conversion reports.

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.

Analyzes codebases and extracts all symbols (functions, classes, methods, interfaces, etc.) from 10+ programming languages into LLM-optimized markdown format. Enables AI assistants to understand entire project structures efficiently without processing full source code.

Security scanning for MCP servers from the inside out. Provides runtime inspection, AST-based static analysis, config audit, dependency analysis, and OWASP MCP Top 10 compliance in a single MCP server.

Bridges Claude Code to Language Server Protocol (LSP) servers to enable semantic code intelligence features like navigation, refactoring, and real-time diagnostics. It supports multiple languages including TypeScript, Python, and Rust with multi-root workspace capabilities.

Self-hosted hybrid code search MCP server with text, symbol, and semantic search layers. Runs locally, no third-party MCP servers, LSP, or SaaS.

Formats SQL queries with support for 14 dialects, keyword casing, and tab width.

Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.