Pylance MCP tool name exceeds Amazon Bedrock 64-character limit

#8155Openmathomp4 创建于 9 天前

Type: Bug NOTE: ChatGPT helped analyze my issue and prepare this issue text since I'm not sure what's happening! I am using VS Code Chat with a custom OpenAI-compatible endpoint backed by LiteLLM. The endpoint exposes Claude models which are routed through Amazon Bedrock. With Pylance enabled, any request to one of these Claude models fails before model execution because a Pylance MCP tool name exceeds Bedrock's 64-character tool-name limit. ## Steps to Reproduce 1. Enable the Pylance extension. 2. Configure a custom OpenAI-compatible language model endpoint in VS Code Chat. 3. Use a Claude model routed through Amazon Bedrock. 4. Leave tool calling enabled. 5. Send any chat/agent request. ## Actual Result The request fails with: ```text Request Failed: 400 litellm.BadRequestError: BedrockException - 1 validation error detected: Value 'activate_fallback_mcp_pylance_mcp_s_pylanceInstalledTopLevelModules_1' at 'toolConfig.tools.85.member.toolSpec.name' failed to satisfy constraint: Member must have length less than or equal to 64 ``` The generated tool name is: ```text activate_fallback_mcp_pylance_mcp_s_pylanceInstalledTopLevelModules_1 ``` The underlying Pylance tool appears to be: ```text pylanceInstalledTopLevelModules ``` but after the additional VS Code/MCP naming is applied, the resulting name exceeds the Amazon Bedrock 64-character limit. I reproduced this with: - Claude Sonnet 4.6 - Claude Sonnet 5 A GPT model through the same LiteLLM endpoint works normally. ## Workaround If I disable the Pylance extension, the same Claude models work successfully through the same endpoint with the same credentials and model configuration. So the endpoint and model routing appear to be working, and the failure is specifically triggered by the Pylance MCP tool registration. ## Expected Result Pylance MCP tools should be usable with providers that impose a 64-character tool-name limit, such as Amazon Bedrock. Possible solutions could include shortening generated MCP tool names, using shorter aliases, or providing a setting to disable Pylance MCP/AI tools while retaining the normal Pylance language-server functionality. 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