What is the key difference between Cognigy AI MCP Management Server and Hubris MCP?

Cognigy AI MCP Management Server belongs to the Conversational AI category with local stdio execution, while Hubris MCP belongs to the Conversational AI category with cloud HTTP/SSE execution.

How do I install Cognigy AI MCP Management Server or Hubris MCP in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Cognigy AI MCP Management Server and Hubris MCP free or paid?

Cognigy AI MCP Management Server operates under a BYOK (Pay Provider Direct) model (API Key required). Hubris MCP operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Cognigy AI MCP Management Server lists 138 tools with 2 views and 2 GitHub stars. Hubris MCP lists 5 tools with 0 views and 0 GitHub stars.

Can I use both Cognigy AI MCP Management Server and Hubris MCP together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

Side-by-Side Model Context Protocol Comparison

Cognigy AI MCP Management Server vs Hubris MCP

In-depth architectural comparison of the Cognigy AI MCP Management Server and Hubris MCP MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

At a Glance & Executive Verdict

Cognigy AI MCP Management Server

Conversational AI · Local stdio

Quality: 60/100 (Good) | Auth: API Key required

Hubris MCP

Conversational AI · Remote HTTP/SSE

Quality: 52/100 (Good) | Auth: No auth required

Verdict Summary: Choose Cognigy AI MCP Management Server if you need specialized Conversational AI tools running via a local process. Choose Hubris MCP if your workspace requires Conversational AI integration with remote web transport. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Cognigy AI MCP Management Server when:

You need dedicated capabilities in the Conversational AI domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: COGNIGY_BASE_URL, COGNIGY_API_KEY, COGNIGY_DEFAULT_PROJECT_ID.
Primary tools included: list_projects, list_flows, get_flow.

Explore Cognigy AI MCP Management Server Details

Choose Hubris MCP when:

You need dedicated capabilities in the Conversational AI domain.
You prefer remote streaming HTTP/SSE transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: models_list, models_search, models_get_pricing.

Feature & Specification Comparison

Specification	Cognigy AI MCP Management Server TsvetanG2 Conversational AI	Hubris MCP Conversational AI
Summary	Management and automation server for the Cognigy.AI conversational AI platform, exposing 132 tools across flows, agents, snapshots, NLU, functions, and deployment. Published to the official MCP Registry. npx mcp-cognigy	OpenAI-compatible LLM gateway for Russia, billed in rubles — catalog, balance, chat via MCP.
Category & Scope	Conversational AI

Tools & Capabilities Breakdown

Cognigy AI MCP Management Server Tools (138)

list_projects

Lists all Cognigy.AI projects accessible by your API key. Use this to discover available projects before working with flows, intents, or other resources.

list_flows

Lists all flows in a Cognigy.AI project. Flows are conversation logic containers. Use this to discover flows before reading or modifying them.

get_flow

Gets detailed metadata about a specific Cognigy.AI flow. Returns flow configuration, locale info, and timestamps. Use this to inspect a flow before modifying it.

get_flow_settings

Gets the settings/configuration of a Cognigy.AI flow. Returns NLU settings, thresholds, and other flow-level configurations. Use this before updating flow settings.

get_latest_log_entries

Gets the latest execution log entries from a Cognigy.AI project. Use this for debugging flow execution, viewing errors, or monitoring agent behavior.

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

Cognigy AI MCP Management Server Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "tsvetang2-cognigy-ai-mcp-management-server": {
      "command": "npx",
      "args": [
        "cognigy-ai-mcp-management-server"
      ],
      "env": {
        "COGNIGY_BASE_URL": "YOUR_COGNIGY_BASE_URL_HERE",
        "COGNIGY_API_KEY": "YOUR_COGNIGY_API_KEY_HERE",
        "COGNIGY_DEFAULT_PROJECT_ID": "YOUR_COGNIGY_DEFAULT_PROJECT_ID_HERE"
      }
    }
  }
}

Hubris MCP Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "hubris-mcp": {
      "url": "https://api.hubris.pw/mcp"
    }
  }
}

Frequently Asked Questions

Cognigy AI MCP Management Server is categorized under Conversational AI and uses a local stdio subprocess. In contrast, Hubris MCP belongs to Conversational AI using remote streaming HTTP/SSE transport. Select Cognigy AI MCP Management Server when you need capabilities focused on conversational ai and Hubris MCP when you require tools for conversational ai.

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