"Integrating Automated Payment Systems" matching MCP servers:

Enables AI-powered access to authoritative design systems knowledge, including W3C standards, WCAG guidelines, and best practices from 188+ curated entries via semantic vector search.

Exposes hybrid document retrieval and evaluation tools from retrieval-lab via MCP, including search_documents, corpus_info, run_evaluation, and search_my_repos, with wire-level conformance tests.

Query 37 EU regulations — from GDPR and AI Act to DORA, MiFID II, eIDAS, Medical Device Regulation, and more — directly from Claude, Cursor, or any MCP-compatible client.

Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON

Enables AI agents to store, search, and relate typed memories with a graph-native knowledge base via the Model Context Protocol.

Enables conversion of webpages to clean markdown with content quality scoring and multi-page crawling for documentation sites. Supports Claude Code, Cursor, and Windsurf with native LangChain and LlamaIndex export formats.

Provides AI agents with database-like operations over LanceDB with automatic BGE-M3 multilingual embedding generation, enabling semantic search, CRUD operations, and safe schema migrations across structured data.

A focused MCP server that provides a single web_search tool for web searches, integrating Tavily and Brave with automatic fallback and key rotation.

A Python package that implements a Model Context Protocol server for integrating with Flowise API, allowing users to list chatflows, create predictions, and dynamically register tools for Flowise chatflows or assistants.

An MCP server integrating Perplexity AI's API to offer advanced search capabilities with support for multiple models and result configuration.

An MCP-compatible server that provides tools for integrating selected Postman API requests, allowing LLMs like Claude to interact with APIs through natural language.

MCP server for integrating manufacturing systems (MES/ERP/quality/maintenance) with LLM agents, enabling event ingestion, incident triage, approval workflows, and RAG-based knowledge retrieval.

A high-performance persistent memory layer for AI agents with multi-modal support, 47 retrieval channels, and 50-tier guardian chains, integrating 12+ memory approaches into a unified architecture.

Enables running durable, traceable AI agents via LangGraph through a universal MCP interface, integrating with Hatchet for orchestration, logging, and retries. Provides tools for knowledge management (ingestion, RAG) and Kubernetes operations (diagnosis, auto-fix).

Enables iterative deep research by integrating AI agents with search engines, web scraping, and large language models for efficient data gathering and comprehensive reporting.

A Model Context Protocol server that retrieves real-time financial and company data using the financialdatasets API. It provides a standardized interface for integrating financial data into agentic frameworks like Agno and Smol Agent.

Chomps through any document, parsing 36+ file formats for AI systems like Claude.

A semantic code retrieval engine for AI agents that enables hybrid search, graph expansion, and token-aware context packing, integrating with MCP to provide precise code context to LLMs.

MCP server for integrating LightRAG with AI tools. Provides a unified interface for interacting with LightRAG API through the MCP protocol.

Enables AI agents to access detailed research findings, implementation patterns, and best practices for building graph-enhanced retrieval-augmented generation systems.