Cognigy Ai Mcp Management Server

io.github.TsvetanG2Published by GitHub account TsvetanG2v0.2.1Updated Oct 24, 2026

MCP server for Cognigy.AI - 132 tools to build, configure & operate conversational AI agents

Overview

AI-generated overview

Local MCP server that lets an assistant build, configure, test and operate Cognigy.AI conversational AI agents through 132 Management API tools.

What you can do
Manage projects, flows, nodes, intents and NLU training, including scoring and audit checks. Run playbooks and regression tests, and inject or reset conversation sessions. Create, restore, diff and promote snapshots, and create, merge, upload or download packages. Configure LLMs, NLU connectors, Knowledge AI stores and sources, functions and extensions. Handle contact profiles, analytics, audit logs, live-agent handover and organization-wide search. Track long-running async tasks and paginate list results.
When to use it
For developers, solution architects and partners who build on Cognigy.AI and want to script agent changes, run NLU training and regression tests, or promote snapshots and packages across environments from an AI assistant instead of the Cognigy UI.
Requirements
Node.js 20 or higher, plus the separately installed @cognigy/rest-api-client peer dependency. A Cognigy.AI account with API access (Trial, SaaS or on-premises). Environment variables COGNIGY_BASE_URL and COGNIGY_API_KEY are required; COGNIGY_DEFAULT_PROJECT_ID is optional. Network access to the Cognigy API endpoint.
Before you install
Requires your Cognigy API key in COGNIGY_API_KEY; keep it out of committed config. Mutating tools default to dryRun true, but real changes to flows, snapshots, packages, profiles and sessions are possible once enabled. The peer dependency is under Cognigy's proprietary license, which you accept by installing it. Contact profile tools handle personal data, including merge and GDPR export.

Installation

In SourceWeft

  1. Open Cognigy Ai Mcp Management Server in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Cognigy.AI Management MCP Server

[CI] [npm version] [npm downloads] [node] [License: MIT] [Glama Score] [MCP Registry] [MCP Badge]

[cognigy-ai-mcp-management-server]

Model Context Protocol server for managing Cognigy.AI virtual agents through the Management API

This is an independent, open-source MCP server and is not affiliated with, endorsed by, or sponsored by Cognigy or NiCE. It requires your own valid Cognigy.AI account and API key, used in accordance with Cognigy's commercial license terms. "Cognigy" and "Cognigy.AI" are trademarks of their respective owners.

What is this?

cognigy-ai-mcp-management-server is a local MCP server that enables AI coding assistants (Claude, Cursor, etc.) to build, configure, test, and operate Cognigy.AI conversational AI agents programmatically.

Instead of clicking through the Cognigy UI, you can now:

  • Create and manage flows, nodes, and intents via natural language
  • Run NLU training and regression tests automatically
  • Deploy snapshots and packages across environments
  • Configure LLMs, Knowledge AI, and integrations

Built for: Developers, solution architects, and SI partners who build on Cognigy.AI.

Requirements

  • Node.js 20.0.0 or higher
  • Cognigy.AI account with API access (Trial, SaaS, or on-premises)
  • API Key generated from Cognigy UI (My Profile → API Keys)

Installation

bash
# 1. Install the Cognigy REST API client (required peer dependency)npm install @cognigy/rest-api-client
# 2. Install this MCP servernpm install -g cognigy-ai-mcp-management-server

Important: The @cognigy/rest-api-client package is licensed under "Cognigy Proprietary License". By installing it, you agree to Cognigy's license terms.

Configuration

Set environment variables before running:

bash
# Required: Your Cognigy API endpointexport COGNIGY_BASE_URL=https://api-trial.cognigy.ai
# Required: Your API key (never commit this!)export COGNIGY_API_KEY=your-api-key-here
# Optional: Default project for operationsexport COGNIGY_DEFAULT_PROJECT_ID=your-project-id

Common Base URLs:

EnvironmentBase URL
Trialhttps://api-trial.cognigy.ai
SaaS EUhttps://api-app.cognigy.ai
SaaS UShttps://api-app-us.cognigy.ai
Dedicatedhttps://api-<company>.cognigy.cloud

MCP Client Configuration

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

json
{  "mcpServers": {    "cognigy": {      "command": "npx",      "args": ["cognigy-ai-mcp-management-server"],      "env": {        "COGNIGY_BASE_URL": "https://api-trial.cognigy.ai",        "COGNIGY_API_KEY": "your-api-key-here"      }    }  }}

Claude Code

Add to .mcp.json in your project root:

json
{  "mcpServers": {    "cognigy": {      "command": "npx",      "args": ["cognigy-ai-mcp-management-server"],      "env": {        "COGNIGY_BASE_URL": "https://api-trial.cognigy.ai",        "COGNIGY_API_KEY": "your-api-key-here"      }    }  }}

Cursor

Add to .cursor/mcp.json:

json
{  "mcpServers": {    "cognigy": {      "command": "npx",      "args": ["cognigy-ai-mcp-management-server"],      "env": {        "COGNIGY_BASE_URL": "https://api-trial.cognigy.ai",        "COGNIGY_API_KEY": "your-api-key-here"      }    }  }}

Available Tools

All Tools

This server provides 132 MCP tools organized by domain:

CategoryToolsDescription
Projects & Flows5List projects, flows, flow settings, logs
Nodes9CRUD operations, search, move, AI output generation
Intents & NLU10Intent management, training, scoring, audit
Endpoints2List and inspect endpoint configurations
Sessions2Inject/reset conversation context
Conversations3Fetch conversations, transcripts
Playbooks & Testing6Run playbooks, regression tests
Snapshots9Create, restore, package, diff, promote
Packages7Create, merge, upload, download
Connections5Manage API connections (secrets redacted)
LLMs7Configure generative AI providers
NLU Connectors5External NLU (Dialogflow, LUIS, etc.)
Knowledge AI21Stores, sources, chunks, connectors (RAG)
Functions9Custom code functions, instances
Extensions6Upload, configure, manage extensions
Contact Profiles11Profile CRUD, merge, export (GDPR)
Analytics4Conversation, call, knowledge metrics
Audit2Audit event logs
Handover7Live agent providers and services
Search1Organization-wide resource search
Tasks2Async task status tracking

Key Features

  • Safe by default: All mutating tools use dryRun: true by default
  • Async-aware: Long-running operations poll until completion
  • Security: API keys only in memory, secrets automatically redacted
  • Pagination: All list operations support limit and skip

Development & Testing

Live API Testing

bash
# Create .env from templatecp .env.example .env# Edit .env with your credentials
# Run development servernpm run dev

Build

bash
npm run build    # Compile TypeScriptnpm test         # Run test suite (49 tests)npm run lint     # Check code style

Regenerate Types (optional)

If you need to update the generated types from a newer Cognigy API:

bash
npm run update:spec   # Download latest OpenAPI specnpm run gen:types     # Regenerate TypeScript types

Important: Dependencies

This package requires @cognigy/rest-api-client as a peer dependency. This means:

  1. You must install it separately (see Installation above)
  2. You accept Cognigy's license terms by installing their package
  3. We do not bundle or redistribute any Cognigy code

You are responsible for:

  • Reviewing and accepting Cognigy's proprietary license terms
  • Having appropriate rights to use the Cognigy API
  • Keeping your API credentials secure

The Cognigy REST API client is the official SDK maintained by Cognigy GmbH and is published on npm under "Cognigy Proprietary License".

License

This MCP server is released under the MIT License. See LICENSE for details.

Note: The MIT license applies only to this MCP server code. Dependencies (particularly @cognigy/rest-api-client) are subject to their own licenses.

Contributing

Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Follow existing code patterns (Zod schemas, dryRun flags, etc.)
  4. Add tests for new tools
  5. Run npm test && npm run build before committing
  6. Submit a Pull Request

Development Guidelines

  • All tools must have Zod input validation
  • Mutating tools must support dryRun flag (default: true)
  • Tool descriptions should be LLM-friendly (1-2 sentences)
  • Never log or expose API keys/secrets
  • Test against mock server before live API

Support


Built with Model Context Protocol SDK

Source: README.md at commit e647397

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

3
  1. v0.2.1LatestOct 5, 2026
  2. v0.2.0Oct 4, 2026
  3. v0.1.4Sep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

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  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts