"Information about 'Linear' or topics related to the term" matching MCP servers:

Exposes 11 agent-native QA tools over stdio so coding agents can discover a project, analyze risk, select the smallest relevant test set, generate and dry-run tests, triage failures, propose tiered heals, analyze flakes, generate quality reports, and evaluate release readiness. Planning and healing tools stay read-only or propose-only, while execution defaults to dry-run, keeping agent actions safe and evidence-backed.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enterprise-grade code intelligence server for AI assistants that analyzes codebases for due diligence, tech debt, security vulnerabilities, and code quality.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

Enables agents to audit and safeguard repositories by detecting dependency pinning issues, license compliance problems, hardcoded secrets, and dead code through MCP tools.

An MCP server that lets AI models run code in 31 languages, evaluate symbolic math and logic problems, and measure complexity—exposed as 48 tools for execution, session management, translation, optimization, and more.

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.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Enables coding agents to audit a Next.js codebase read-only, checking routes, Prisma models, environment variables, and locale consistency via MCP tools.

Enables scanning repositories for TODO and FIXME markers while avoiding false positives in strings and URLs, then reports each marker’s age, author, and staleness using git blame and history. It also counts suppression signals, long functions, and commented-out code inside real comments.

Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.

MCP server for automatic Storybook story generation, component analysis, and validation. Auto-detects React frameworks and syncs component documentation.

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.

Enables developers and agents to determine what licenses a project's dependencies use and whether shipping is permitted, combining SPDX parsing, installed metadata, lockfile readers, a compatibility table, and a policy engine whose verdicts always carry reasons.

Enables an agent to mine a repository's git history and answer questions a new teammate would ask: which files are riskiest based on churn, recency and author breadth, who actually knows each file based on surviving lines, which files secretly change together, which directories depend on one person, and what recent commits mean for release notes. All analysis runs through a read-only server sandboxed to a single directory.

Enables an AI to risk-review Terraform and OpenTofu plan files over MCP stdio by summarizing plans, ranking dangerous changes, diffing resources with secrets masked, and comparing two plans without running Terraform.

Enables AI agents to inspect git working trees and history for exposed credentials without letting raw secrets reach the model, with false-positive filtering, baseline support, and remediation guidance.

Enables an AI to statically audit GitHub Actions workflow files, parsing YAML with accurate line numbers and reporting findings about on: key quirks, expression injection risks, unpinned actions, effective token permissions, and cron scheduling.

Enables an AI to statically lint Dockerfiles and compose files without Docker by parsing their true structure, reporting line-numbered findings with concrete fixes, and analyzing cache order, .dockerignore matching, and safe fix previews as diffs.

Exposes a set of CLI tools (test generation, documentation generation, linting, test running, code search) to AI assistants via MCP, allowing them to perform these tasks through natural language.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

MCP server that exposes pre-extracted facts about code behavior, design decisions, and assumptions to AI agents, saving time and tokens by avoiding direct source file reading.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

truth is a deterministic fact-checker for the claims an AI coding agent makes about its own work.

Enables Claude to explore, analyze, and answer questions about any public GitHub codebase by connecting to DeepWiki's AI-powered documentation.