"MCP server that provides both prompts and resources" matching MCP servers:

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

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Exposes MAID Runner validation tools (validate, snapshot, test) as MCP tools, resources, and prompts for AI agents like Claude Code and Aider, enabling seamless integration with AI development workflows.

MCP server that allows reading inside Java archives (classes, APIs, sources, resources, bytecode) without extraction, with focused tools to minimize context window noise.

Enables logical entailment and satisfiability checks by dispatching formal SMT-LIB queries to both Z3 and cvc5, returning auditable solver verdicts, counterexamples, and caveats.

A Model Context Protocol server that accelerates CodeIgniter-inspired PHP framework development by generating, validating, and maintaining idiomatic MVC plus Services/Repository code via 7 tools and 4 resources.

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

Provides real-time security risk assessment for AI coding prompts, analyzing potential dangers, blast radius, and complexity before code execution in Cursor.

Provides tools to retrieve deterministic prompts for rewriting any Node.js project to production-quality TypeScript, supporting incremental and single-pass workflows.

An MCP server that provides tools for getting second opinions or detailed code reviews from Gemini 2.5 Pro by embedding file contents in prompts, allowing it to handle large codebases with extensive context.

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

Automatically enhances developer prompts with quality requirements, codebase context, and architectural patterns, then orchestrates other MCP servers to ensure AI coding assistants produce high-quality, structured code that follows best practices and security standards.

Hybrid MCP server that combines Graphify’s structural code graphs with Understand-Anything’s semantic knowledge bases, exposing both as MCP tools for code analysis and natural-language questioning.

Enables AI agents to understand, inspect, create, validate, build, and document Jekyll component frameworks through Jekyll-aware tools, resources, prompts, sandboxed filesystem access, and configurable write modes.

Enables evaluating Python projects against a deterministic quality bar using analyzer findings, per-dimension scores, and a review verdict, exposed through MCP tools, resources, and prompts. Users can run evaluations, inspect rules, and list analyzers to assess code readiness for review.

Enables semantic code search across local projects and Git repositories using AI embeddings with ChromaDB. Supports both OpenAI and local Ollama models for private, enterprise-ready code analysis and similar code discovery.

A Python MCP server that exposes the Graphify knowledge graph as MCP tools, prompts, and resources, enabling AI assistants to explore codebases through a token-budgeted, structural graph during development.

An MCP server that provides LLMs with access to Equinox documentation and tools to validate Equinox module code. It supports both online documentation fetching from GitHub and offline access through local files.

Harvests React components from Aceternity UI and Shadcn UI, fetching code and metadata to generate integration prompts for AI agents.