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cognigy-ai-mcp-management-server

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Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

A3.5/5.0

Scored across 138 tools

Disambiguation3/5

Most tools have distinct purposes, but several pairs overlap noticeably (e.g., score_utterance vs generate_nlu_scores both score utterances against NLU intents; create_package, package_snapshot, and promote_snapshot all package resources). Descriptions help, but with 138 tools the agent can still misselect among similar-sounding operations.

Naming Consistency5/5

Every tool follows a consistent snake_case verb_noun pattern (e.g., list_flows, get_node, create_intent, delete_knowledge_store). Minor variations like get_nodes vs get_node are natural, and no mixed conventions appear.

Tool Count1/5

138 tools far exceeds reasonable bounds for an agent-facing server, even given Cognigy.AI's broad platform. This extreme count creates a high cognitive load and increases selection errors, matching the rubric's 50+ tools criterion for an extreme mismatch.

Completeness3/5

Coverage is broad across many resources (NLU, knowledge, contacts, snapshots, packages, functions, LLMs), but notable gaps exist: no create_flow/update_flow/delete_flow, no create_endpoint/update_endpoint/delete_endpoint, and no update_flow_settings. These missing core CRUD operations for central resources limit end-to-end management workflows.

Maintenance

ActivityActive
ResponsivenessNo issues

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