"Ram" matching MCP servers:

Unified MCP server: hybrid search + code graph + semantic memory. 10 tools, <350MB RAM, fully local. No API keys.

Enables AI assistants to access Ramp's developer documentation and API schemas through natural language queries. Provides contextual answers about API endpoints, authentication methods, data relationships, and implementation patterns for developers building on Ramp's platform.

Integrates SEO analysis and Google Search Console data directly into Claude Code and Cursor. Performs real-time site audits, detects technical SEO issues, validates meta tags, generates structured data, and provides AI-powered recommendations for both production sites and local development servers.

A Model Context Protocol server that enables LLMs to interact with Ramp's financial data by retrieving, analyzing, and running tasks through Ramp's Developer API, using an in-memory SQLite database to overcome token limitations.

An MCP server that evaluates product designs against Dieter Rams' 10 principles of good design, providing scores, feedback, and improvement suggestions.

Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.

A self-hosted MCP server that fetches live documentation and performs code audits using real-time authoritative references to prevent AI hallucinations. It provides tools for searching documentation across 330+ libraries and scanning local source code for security, performance, and accessibility issues.

Enables AI coding agents to search public design-system catalogs and retrieve only the relevant tokens or sections for a chosen brand, so generated UI matches a specified visual style instead of generic AI output.

Provides comprehensive access to Roam Research's API functionality. This server enables AI assistants like Claude to interact with your Roam Research graph through a standardized interface.

MCP server that migrates SAP Module Pool programs to RAP applications interactively, using AI and SAP ADT REST APIs with human approval at each step.

Speeds up coding agents by predicting and pre-executing upcoming tool calls, then safely returning validated cached results to eliminate wait time.

Grok asked for MCP on a URL. This is it. First MCP server built for Grok URL-based • Zero config • Just works

Enables AI agents to search and retrieve jam-nodes documentation, including node info, API references, and guides, via MCP tools without loading everything into context.

.FAF (Foundational AI-context Format) with 50+ tools - Only Persistent project context that integrates seamlessly with Claude Desktop workflows. Officially merged (#2759) Anthropic MCP server.

Enables querying LlamaCloud document indices using retrieval-augmented generation, providing intelligent answers with sources directly in Cursor IDE.

Persistent project context MCP server that syncs a single .faf file to all AI tool formats (Cursor, Windsurf, Cline, etc.), enabling eternal bi-sync and optimized context for AI assistants.

Persistent project context for Google Gemini. 12 MCP tools for .faf Project DNA — auto-detect your stack, validate, score, and sync across CLAUDE.md, GEMINI.md, and AGENTS.md. Python/FastMCP. IANA-registered format (application/vnd.faf+yaml). 183 tests. One file, every AI platform.

Enables running a minimal MCP server over stdio that manually implements JSON-RPC, exposing an add tool so users can observe the handshake, tool listing, and tool call cycle without the official SDK.

Connect your AI coding assistant to TestRail to manage test cases, runs, results, and more directly from VS Code, Cursor, Claude Desktop, or Claude Code.

A TypeScript MCP server that allows querying documents using LLMs with context from locally stored repositories and text files through a RAG (Retrieval-Augmented Generation) system.