"Information about Flowable (e.g., workflow and business process management tool)" matching MCP servers:

Enables seamless integration between Claude AI and Dify Workflow through the Model Context Protocol, allowing Claude to dynamically access and execute Dify Workflow operations via natural language.

Enables querying company knowledge base using RAG, providing accurate answers from internal documents via MCP.

An MCP server exposing internal business operations as tools — task management (create, list, update status) and RAG-style semantic search over an internal knowledge base (leave, expense, and onboarding policies) that any MCP-compatible AI agent can call directly for grounded, non-hallucinated answers.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

A custom MCP tool that integrates Perplexity AI's API with Claude Desktop, allowing Claude to perform web-based research and provide answers with citations.

MCP server that enables persistent, hybrid, local memory for LLM agents, with vector + BM25 search, knowledge graph, and policy-driven retention, providing token-budgeted context injection for AI assistants.

An MCP (Model Context Protocol) server that chains calls to other MCP tools, reducing token usage by allowing sequential tool execution with result passing

A universal MCP tool gateway that manages multiple remote tool processes, enabling LLMs to dynamically invoke web scraping, summarization, and knowledge retrieval through standardized Function Calling.

Enables dynamic tool discovery and loading for Claude using BM25, regex, and semantic search algorithms. It supports managing a catalog of over 10,000 tools with minimal context overhead and provides a REST API for tool management.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Enables MCP-compatible clients to perform retrieval-grounded Q&A over FordA dataset notes and safe arithmetic calculations through callable tools.

Exposes search over internal documents and company lookup via authenticated API, enabling LLMs to access firm files and data.

A Model Context Protocol server that provides Claude with a dedicated space for structured thinking during complex problem-solving tasks, helping improve its reasoning capabilities.

This read-only MCP Server allows you to connect to Dynamics 365 Business Central data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Jira Service Management (beta): https://www.cdata.com/download/download.aspx?sku=GKZK-V&type=beta

A tool that integrates process mining capabilities with Claude AI, allowing users to analyze event log data from PostgreSQL databases through natural language interfaces in Claude Desktop or Cursor.

Transforms prompts into Chain of Draft (CoD) or Chain of Thought (CoT) format to enhance LLM reasoning quality while reducing token usage by up to 92.4%, supporting multiple LLM providers including Claude, GPT, Ollama, and local models.

An evidence-first Model Context Protocol server for private business documents and structured datasets, preserving original files and source lineage.