"Information about Adobe After Effects or its uses" matching MCP servers:

Enables AI-powered generation, customization, and documentation of its-just-ui React components. Provides tools for component generation, theme management, form creation, responsive layouts, and accessibility guidance.

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.

A local guardrail MCP server that checks agent-written code against a repo's own patterns — learned statistically from its git history, no LLM.

Contract-first programming language with a local MCP server for checking types, effects, capabilities, and contracts in agent-written modules. Its review tool compares before and after source sets and returns receipts for new authority, weaker promise tiers, and new Guarded runtime obligations.

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

MCP server for verifying AI agent claims vs reality — single-transcript inline grounding-check that flags when an agent's response states facts not in the input context, when its code silently swallows exceptions and substitutes mock data, or when its multi-turn transcript contains contradictions or unverified completion claims. Sub-second, local, free, no API calls.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

Helps AI coding agents migrate Angular Reactive Forms to Signal Forms by locating form constructs, distinguishing mechanical renames from judgment calls, and providing verified before/after recipes. It only detects and advises, never edits source code.

MCP server that runs JetBrains' ReSharper command-line tools for code inspection and cleanup, exposed to C# coding agents over stdio.

Enables a coding agent to get short, token-efficient answers about a project through grouped searches, focused symbol or section reads, and bounded read-only script output, with safety limits on paths, secrets, commands, and response size.

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.

Analyzes a local codebase and exposes its structure, per-file summaries, dependency graph, and complexity hotspots as tools for MCP clients like Claude.

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.

Enables AI agents to search and retrieve details about Odoo code elements (models, fields, views, etc.) with exact file locations using MCP tools.

A deterministic symbol oracle over a locally built index of the repository: whether a symbol exists, what a file declares, and what changed structurally since the last snapshot. It also ships a PreToolUse guard that stops an Edit/Write referencing a function, constant or type the repo does not declare, before the write lands rather than after the build fails. No LLM, no API keys, no network, no l

A static code generation server for GSAP animations. It provides 18 tools to generate tween, timeline, easing, plugin effects (ScrollTrigger, SplitText, MorphSVG, etc.), and developer utilities without any GSAP runtime dependency.

Enables AI coding assistants to retrieve exact, version-correct icon names and import statements from the icon packages a project actually uses, eliminating guesses and build failures.

Provides coding agents with a compact map of a TypeScript/TSX codebase, enabling direct answers about symbol locations, imports, dependencies, and references while reducing token usage.

Evidence-backed, read-only codebase diagnostics for coding agents: secrets, dependency, RLS, and source-impact audits with a verify loop and PR review verdicts. Never writes files or uses the network by default.

A mcp server to allow LLMS gain context about shadcn ui component structure,usage and installation

Enables coding agents to discover which pinned dependencies changed after their training cutoff, and to search those changes in their own words to get matching diffs, changelog items, and upgrade notes. It also writes a short notes block into AGENTS.md or CLAUDE.md and flags outdated API usage after each edit.

Technology-aware MCP server for Magento 2 and Adobe Commerce with intelligent indexing and search, enabling AI assistants to search, navigate, and understand codebases via semantic search and domain-specific pattern detection.

A local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.

Local-first, code-aware engineering cognition for AI coding agents - persistent memory, contextual retrieval, and continuous cognition about your codebase.

A TypeScript/JavaScript refactoring MCP server that uses the TypeScript compiler to perform safe, type-aware code transformations such as renaming, extracting functions, and organizing imports across your codebase.

Rarefaction is a Model Context Protocol (MCP) server that gives a coding agent the call graph and code context for one symbol straight from the project's language server (Language Server Protocol, LSP). Ask about a function, method or type and get, in one call: its signature and doc, its body, who calls it (tests marked), what it calls, who implements it, the tests that reach it and the short list