invoke_endpoint.py — Hugging Face MCP Resource
invoke_endpoint.py
is one of 149 resources on the
Hugging Face
MCP server. Connect the server and your client can attach it as context.
by client
How to attach invoke_endpoint.py from your client
- Claude Code Hugging Face Resource/invoke_endpoint.py run in your project directory
- Claude Desktop Hugging Face Resource/invoke_endpoint.py ~/Library/Application Support/Claude/claude_desktop_config.json
- Cursor Hugging Face Resource/invoke_endpoint.py ~/.cursor/mcp.json
- VS Code Hugging Face Resource/invoke_endpoint.py .vscode/mcp.json
- Zed Hugging Face Resource/invoke_endpoint.py ~/.config/zed/settings.json
- Windsurf Hugging Face Resource/invoke_endpoint.py ~/.codeium/windsurf/mcp_config.json
- Cline Hugging Face Resource/invoke_endpoint.py ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
- Gemini CLI Hugging Face Resource/invoke_endpoint.py ~/.gemini/settings.json
- Grok Hugging Face Resource/invoke_endpoint.py .mcp.json (in your project root)
- ChatGPT Hugging Face Resource/invoke_endpoint.py Settings → Connectors → Advanced → Developer mode
- Claude.ai Hugging Face Resource/invoke_endpoint.py Settings → Connectors → Add custom connector
- LangChain Hugging Face Resource/invoke_endpoint.py pip install langchain-mcp-adapters
Other resources on this server
- hf-cli
- hf-cloud-aws-context-discovery
- hf-cloud-python-env-setup
- requirements.txt
- check_versions.py
- setup_env.py
- hf-cloud-sagemaker-deployment-planner
- hf-cloud-sagemaker-iam-preflight
- minimum-permissions.json
- trust-policy.json
- check_role.py
- create_role.py
- hf-cloud-sagemaker-production-defaults
- deployment-template.md
- _common.py
- deploy.py
- deploy_async.py
- deploy_ic.py
- teardown.py
- hf-cloud-serving-image-selection
- model-to-image.md
- mirror_image.py
- hf-mem
- huggingface-best
- huggingface-community-evals
- .env.example
- USAGE_EXAMPLES.md
- inspect_eval_uv.py
- inspect_vllm_uv.py
- lighteval_vllm_uv.py
- huggingface-datasets
- huggingface-gradio
- examples.md
- huggingface-llm-trainer
- gguf_conversion.md
- hardware_guide.md
- hub_saving.md
- local_training_macos.md
- reliability_principles.md
- trackio_guide.md
Read from the server itself, by connecting to it and calling resources/list on 24 September 2026.
A listing does not declare its resources, so asking is the only way to know them, and this
is what the server actually offers rather than what its listing claims. Names only are
stored; connect the server for each resource's type and contents.