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Standalone chat assistant powered by Azure AI models with support for multiple LLM providers (Azure, OpenAI, Anthropic, Google, DigitalOcean, Bedrock, Puter). Provides chat, configuration, model listing, and conversation management tools.
This MCP server has severe definition quality gaps. While 5 tools are defined, most lack proper schemas, parameter descriptions are minimal or missing, and descriptions fail to guide LLM selection. The 'chat' and 'configure' tools have some parameter details but lack complete input schemas in the visible code. The 'reset', 'clear_cache', and 'models' tools have empty input schemas with no parameters documented. Error handling guidance is absent across all tools. Tool naming is reasonable (verb-noun pattern) but the schemas and descriptions do not meet production standards for agent tool composition. No output schemas are documented. This server would cause LLM confusion around tool selection and proper invocation.
Send a message to the LLM, get a response (with conversation history)
Clear the in-memory response cache
View/change settings dynamically (model, API key, region, etc.)
List available models and test connectivity
Clear conversation history
Three tools (reset, clear_cache, models) have empty input schemas with no parameters documented. Per hard scoring rules, schema score must be 0 when input schemas are absent.
Output schemas are completely undocumented for all tools. LLMs cannot plan downstream calls or extract required data without knowing what fields to expect.
The 'configure' tool accepts free-form 'key' and 'value' string parameters with no enum constraint or validation guidance. No documentation of valid keys (model, api_key, endpoint, temperature). LLM will hallucinate invalid configuration keys.
No error handling guidance. Tools have no documented recovery paths. If 'chat' fails due to API error, or 'configure' receives an invalid key, the LLM has no actionable next step.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 41 | 2026-07-28+ | v2 |
Tool descriptions are too brief (30-50 characters). They lack context for LLM selection and do not explain WHEN to use each tool vs alternatives. E.g., 'Clear the in-memory response cache' tells an LLM nothing about when cache clearing is needed.
The 'chat' tool description does not explicitly state that it maintains conversation history or that previous messages affect subsequent responses. This is critical for the LLM to understand tool state and idempotency.
'configure' tool description lacks documentation of parameter dependencies and side effects. Changing 'api_key' or 'endpoint' mid-conversation could break the state. No guidance on when to call this vs when values persist.
Parameter descriptions in 'chat' are incomplete. 'temperature' is described as 'Optional temperature override (0.0-2.0)' but does not explain that higher values increase randomness or when an LLM should use this override. 'max_tokens' lacks guidance on typical ranges.