"CLine MCP Server Information or Setup" matching MCP servers:

Enables auditing a repository's Claude Code setup, scoring it from 0 to 100, and scaffolding agents and hooks to fix issues.

Enables AI coding agents to ground dependency setup, compatibility checks, and major-version migration advice in a project's real runtime, lockfiles, and config files. It parses local project state and npm registry metadata deterministically, then returns tag-pinned install commands, breaking changes, and upgrade steps rather than generic documentation.

An MCP server that enables Cline to analyze binaries using Binary Ninja with a Personal License through a bridge implementation.

Enables AI assistants to import binaries into Ghidra, trigger analysis, browse functions, symbols, strings, and imports, and read decompiled C code and disassembly via MCP tools.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

Fast pre-commit dependency gate for AI-assisted code changes. Answers "is this safe to commit?" with a PASS/WARN/BLOCK verdict in seconds, so you can catch risky blast radius before a bad commit, not after it. No database, no heavy setup.

MCP server that provides npm package information for AI agents during TypeScript development.

Exposes CT's C/C++ verification tools - project setup, analysis, test generation and execution, coverage, reporting - to an MCP client. Requires a local CT 2026.06 or later installation; without one the server reports zero tools.

A fully local RAG MCP server for semantic code search and code intelligence, using AST-level chunking and hybrid search to pinpoint functions, classes, and APIs. No cloud, no API keys, zero setup.

Enables coding agents to turn existing Compose and SwiftUI previews into a static Storybook-style gallery, including setup diagnosis, coverage analysis, and generating or building the gallery. It automates the creation of browsable component catalogs for native mobile apps without requiring a SaaS account.

Enterprise-grade (40m+ lines) codebase intelligence in a zero-setup, private and local MCP: managed indexing, hybrid semantic search, polyglot code dependency graphs, and DB/API/infra knowledge. Benchmark: 61% less tokens, 84% fewer calls, 37x faster than standard AI grep.

A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup

Enables local detection of protected health information in source code before it reaches LLM prompts, log statements, or analytics calls.

A Model Context Protocol server that provides PureScript development tools for AI assistants, enabling code analysis, type lookups, and IDE server management without requiring heavy IDE setup.

Enables AI coding agents to perform fast regex/text and structural AST searches across codebases, find symbols, list files, and safely preview or apply refactors. It unifies ripgrep and ast-grep with pagination, gitignore-aware defaults, and fallback engines for zero-setup code search.

The server facilitates natural language interactions for exploring and understanding codebases, providing insights into data models and system architecture using a cost-effective, simple setup with support for existing Claude Pro subscriptions.

An MCP server that bridges tools like Cline to SAP ABAP systems, enabling retrieval of source code, table structures, and more via the ADT protocol.

An MCP server for gitingest. It allows MCP clients like Claude Desktop, Cursor, Cline etc to quickly extract information about Github repositories including repository summaries, project directory structure, file contents, etc

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

Federates UI component registries, enabling AI agents to fetch exact component code, dependencies, and setup prerequisites directly into the workspace. Includes sandboxed previews, anti-slop layout auditing, and offline-to-cloud telemetry sync.

A context provider that serves as an AI version of Chris's programming knowledge and practices. Enables AI utilities like Claude and Cline to search and access coding guidelines, rules, and context for JavaScript, TypeScript, React, and various development frameworks.

Enables agents to query TypeScript and JavaScript code intelligence—type diagnostics after edits, go-to-definition, references, hover information, and document symbols—through MCP tools.

Enables automatic project understanding and context injection for OpenCode and Antigravity, detecting project type and refreshing knowledge incrementally without per-project setup.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

Runs a one-click security audit on your MCP setup, scanning packages for vulnerabilities and assigning a score from 0-100 with actionable recommendations.

An MCP server that wraps the local Grok Build CLI, enabling Codex to delegate code reviews, bounded coding tasks, and setup diagnostics to Grok for a second opinion or parallel processing.

An MCP server that enables AI assistants to parse Xcode and Swift build outputs into structured, token-efficient formats like JSON or TOON. It provides tools for executing build commands and extracting detailed diagnostic information such as errors, warnings, and test failures.

Exposes a Dockerfile auditing engine to AI assistants, letting them scan a Dockerfile for the 32 deterministic layer-aware rules, print a stage/layer map showing what each layer adds or deletes, explain any rule's rationale and fix, and list available rules. Findings include file:line evidence so agents can surface and triage image-safety issues directly in Claude Code, Cursor, or Cline.