"Framework7" matching MCP servers:

Review and rewrite LangChain, LlamaIndex, Ollama, and XRPL code against current APIs, plus runnable examples, import lookup, and XRPL tx skeletons that never submit. Live docs included. $0.001 USDC on Base or 1000 drops XRP.

Gives AI assistants a read-only, offline interface to the FinOps Foundation's published guidance — its principles, phases, domains, 22 capabilities with Crawl/Walk/Run maturity assessments, personas, and an 88-entry KPI library — so FinOps questions are answered with the Foundation's own text and formulas rather than improvised ones. It exposes 11 tools, document resources, and four guided prompts over stdio, with every response carrying its source URL and license.

MCP server enabling a florr.io game agent with YOLO vision, entity prediction, combat assessment, and local knowledge base for autonomous gameplay.

A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.

Contract-driven test enforcement and reporting for LLM-generated code via MCP, VS Code, Copilot CLI, Claude, Cursor, or Python SDK.

Unified MCP server integrating NIST and OWASP security frameworks with live vulnerability data, enabling security searches, compliance mapping, threat modeling, and checklist generation.

A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.

An extensible framework that exposes quantitative research functions and financial data connectors, such as FRED, via an MCP server. It enables users to perform complex financial modelling, data retrieval, and autonomous research loops with built-in guardrails and pluggable components.

Enables LLM agents to programmatically inspect hardware resources, run in-memory inference benchmarks, list supported fMRI studies, and retrieve cortical and subcortical atlas region indices via JSON-RPC 2.0.

Enables AI agents to act as a state-driven tutoring engine over MCP, with server-side mastery estimation, prerequisite checks, evidence-based assessment, and FSRS spaced review scheduling.

Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.

Provides a runnable local stdio Python server scaffold that coding agents extend into custom tool integrations by describing an idea and letting the agent investigate, build, test, and install it. Ships with no prebuilt tools, so it enables guided, agent-assisted creation of MCP tools connected to external APIs, databases, or websites while writes stay disabled until explicitly agreed.