"How to access the BASH shell" matching MCP servers:

coldstart gives coding agents durable memory of a specific codebase, with no embeddings, no vector store, and no API key. Agents write notes after real tasks — what a file is for, how a flow spans files, which invariants hold — and those notes are surfaced automatically to a later session whose task matches, so nothing gets rediscovered from scratch. Every note is anchored to real files by content

Call graph MCP server for Rust, Python, TypeScript, TSX, and JavaScript. Every caller and callee carries a resolution field showing how the reference was matched to a definition, plus multi-hop impact analysis for refactoring. Local-only, single binary, no network egress. Benchmarked against grep, ripgrep, and ctags on a 120-item hand-verified golden set, including the cases where it loses.

MCP server that provides shell script linting via ShellCheck. Allows AI agents to analyze shell scripts for common errors, stylistic issues, and potential bugs.

Gives AI coding tools access to the CSS cascade the way DevTools does — which rules matched, which won, where each came from.

Enables AI assistants to access Macroforge documentation, validate TypeScript code with @derive decorators, expand macros, and retrieve macro documentation.

Enables AI assistants to directly invoke higpertext-cli capabilities as validated MCP tools, covering grep search, git diff and ls-files, smart reading, code skeletonization, knowledge lookup, memory management, committing, secret scanning, and quality resolution without routing through Bash.

Scans GitHub Actions workflow files for dangerous triggers, template injection, unpinned actions, excessive permissions, and secrets in shell commands before they are committed, exposing the checks as MCP tools for agents.

Enables AI agents to formally verify constant-time, masking, and patch completeness properties of Verilog hardware designs, providing concrete leakage signals and next-step guidance.

A lightweight MCP server that provides 40 tools for TypeScript/JavaScript refactoring and code intelligence, directly mapping to TypeScript's tsserver protocol commands for accurate structural changes and workspace analysis.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

A secure MCP server that exposes local repository context to ChatGPT/Codex with read-only access, path validation, and no generic shell.

Enables AI coding agents to interact with TypeScript projects through compiler-level code intelligence, providing tools for navigation, type information, diagnostics, refactoring, and semantic search.

An MCP server that enables AI agents to move TypeScript files and directories while automatically updating all affected imports using a persistent tsserver instance. This ensures atomic, error-free refactoring that maintains project integrity without manual intervention or wasted tokens.

Analyzes codebases for cross-platform compatibility issues, detecting platform-specific APIs, file path problems, line ending inconsistencies, and shell command incompatibilities across Windows, macOS, and Linux.

A TypeScript/Node.js MCP toolkit with servers for code search, docs, databases, OpenAPI, Git, and shell-based developer workflows.

Enables AI assistants to execute SuperSQL queries on data files and SuperDB databases without shell escaping issues. Supports querying, schema inspection, database pool management, and provides LSP features for code completion and documentation.

Implements the Model Context Protocol (MCP) over HTTP to provide remote access to BluestoneApps coding standards and React Native code examples.

Enables full-stack compiler development across the hw-native-sys workspace by combining repository operations (git health, code search, task running) with a knowledge layer for architecture docs, task routing, and abstraction/pass pipeline information.

An MCP server leveraging the Rust-based ty type checker to provide AI models with high-performance, semantic Python code analysis and structural navigation. It enables precise symbol searching, cross-file renaming, and diagnostic reporting to improve code understanding and editing accuracy.

Enables static analysis and code smell detection by connecting to an external analysis API.