"TOML" matching MCP servers:

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.

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CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments

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.

Enables binary comparison capabilities by leveraging IDA Pro and BinDiff to analyze similarities and differences between files. Users can perform automated function analysis to identify changed functions and compare original binaries against patched versions.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables LLMs to perform binary analysis using Ghidra in headless mode, extracting functions, pseudocode, structs, and enums from binaries for interactive reverse-engineering.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

An MCP server for the OpenAI Codex CLI that provides coding assistance with multi-turn session management and reasoning depth control. It enables users to perform code analysis, generation, and refactoring through Claude with native resume support for conversational context.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

Provides AI agents with a function-level dependency graph of the codebase through 30 MCP tools, enabling structural queries about code dependencies, callers, and impact analysis.

Integrates GitHub Copilot CLI with MCP clients to offer various coding assistance tools including asking questions, explaining code, suggesting commands, debugging, refactoring, generating tests, and reviewing code.

Enables LLMs to analyze Python repositories structurally via AST and call graphs, providing code search, symbol lookup, change-impact analysis, workflow tracing, and explanation without embeddings.

Audits dbt Core projects for migration blockers and generates actionable guidance for migrating to dbt Cloud, including auto-fixing deprecated syntax.