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TsvetanG2/cognigy-ai-mcp-management-server

by Various

MCP server for Cognigy.AI - 132 tools that let Claude, Cursor & other AI assistants build, configure, test & operate conversational AI agents via the Model Context Protocol.

MCP

TsvetanG2/cognigy-ai-mcp-management-server

Added 3 Sept 2026

#agents #agentskills #claude #claude-code #claude-code-skill #cognigy #cognigy-ai #conversational-ai

Overview

MCP server for Cognigy.AI. Exposes 132 tools that let Claude, Cursor and other AI assistants build, configure, test and run conversational AI agents via the Model Context Protocol. Written in TypeScript.

Best for

Best for
Developers exploring agent management through MCP who already use Cognigy.AI

Use cases

  • Build and configure Cognigy.AI agent flows from an MCP client
  • Run tests and operational tasks on agents through Claude or Cursor
  • Manage agent settings programmatically using natural language prompts

Notes

MCP server for Cognigy.AI. Exposes 132 tools that let Claude, Cursor and other AI assistants build, configure, test and run conversational AI agents via the Model Context Protocol. Written in TypeScript.

2 stars on GitHub. Last updated 2026-09-02. Licensed MIT.

Use cases

  • Build and configure Cognigy.AI agent flows from an MCP client
  • Run tests and operational tasks on agents through Claude or Cursor
  • Manage agent settings programmatically using natural language prompts

Pros

  • Broad toolset with 132 tools covering the agent lifecycle
  • Works with multiple MCP clients like Claude and Cursor
  • TypeScript codebase that integrates into standard Node.js tooling

Cons

  • Very small adoption with only 2 GitHub stars
  • Documentation and community support are likely limited
  • Status and reliability are uncertain for production use

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Broad toolset with 132 tools covering the agent lifecycle
  • Works with multiple MCP clients like Claude and Cursor
  • TypeScript codebase that integrates into standard Node.js tooling

Cons

  • Very small adoption with only 2 GitHub stars
  • Documentation and community support are likely limited
  • Status and reliability are uncertain for production use

Pairs with

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