unichat
Chat with an AI assistant to review documents, evaluate proposals, or answer questions by providing a system message and user query.
Instructions
Chat with an assistant. Example tool use message: Ask the unichat to review and evaluate your proposal.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| messages | Yes | Array of exactly two messages: first a system message defining the task, then a user message with the specific query |
Implementation Reference
- src/unichat_mcp_server/server.py:249-271 (handler)The handler function for the 'unichat' tool. It validates the tool name, checks the messages input, calls the UnifiedChatApi to generate a response using the specified model, formats the response, and returns it as TextContent.@server.call_tool() async def handle_call_tool(name: str, arguments: dict | None) -> list[types.TextContent]: if name != "unichat": logger.error(f"Unknown tool requested: {name}") raise ValueError(f"Unknown tool: {name}") try: logger.debug("Validating messages") validate_messages(arguments.get("messages", [])) response = chat_api.chat.completions.create( model=MODEL, messages=arguments["messages"], stream=False ) response = format_response(response.choices[0].message.content) return [response] except Exception as e: logger.error(f"Error calling tool: {str(e)}") raise Exception(f"An error occurred: {e}")
- The JSON schema defining the input structure for the 'unichat' tool, requiring an object with a 'messages' array of exactly two items (system and user roles).inputSchema={ "type": "object", "properties": { "messages": { "type": "array", "items": { "type": "object", "properties": { "role": { "type": "string", "description": "The role of the message sender. Must be either 'system' or 'user'", "enum": ["system", "user"] }, "content": { "type": "string", "description": "The content of the message. For system messages, this should define the context or task. For user messages, this should contain the specific query." }, }, "required": ["role", "content"], }, "minItems": 2, "maxItems": 2, "description": "Array of exactly two messages: first a system message defining the task, then a user message with the specific query" }, }, "required": ["messages"], },
- src/unichat_mcp_server/server.py:210-248 (registration)The list_tools handler that registers and exposes the 'unichat' tool, including its name, description, and input schema.@server.list_tools() async def handle_list_tools() -> list[types.Tool]: return [ types.Tool( name="unichat", description="""Chat with an assistant. Example tool use message: Ask the unichat to review and evaluate your proposal. """, inputSchema={ "type": "object", "properties": { "messages": { "type": "array", "items": { "type": "object", "properties": { "role": { "type": "string", "description": "The role of the message sender. Must be either 'system' or 'user'", "enum": ["system", "user"] }, "content": { "type": "string", "description": "The content of the message. For system messages, this should define the context or task. For user messages, this should contain the specific query." }, }, "required": ["role", "content"], }, "minItems": 2, "maxItems": 2, "description": "Array of exactly two messages: first a system message defining the task, then a user message with the specific query" }, }, "required": ["messages"], }, ), ]
- Helper function to validate the messages input for the unichat tool, ensuring exactly two messages with correct roles.def validate_messages(messages): logger.debug(f"Validating messages: {len(messages)} messages received") if len(messages) != 2: logger.error(f"Invalid number of messages: {len(messages)}") raise ValueError("Exactly two messages are required: one system message and one user message") if messages[0]["role"] != "system": logger.error("First message has incorrect role") raise ValueError("First message must have role 'system'") if messages[1]["role"] != "user": logger.error("Second message has incorrect role") raise ValueError("Second message must have role 'user'")
- Helper function to format the chat API response into the required TextContent type.def format_response(response: str) -> types.TextContent: logger.debug("Formatting response") try: formatted = {"type": "text", "text": response.strip()} logger.debug("Response formatted successfully") return formatted except Exception as e: logger.error(f"Error formatting response: {str(e)}") return {"type": "text", "text": f"Error formatting response: {str(e)}"}