MCP server · TensorFlow
tensorflow-serving
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⚠ Proposed MCP surface. No official hosted MCP server was found for TensorFlow. The tools below are a candidate set derived from this provider's API, and the link points at the source descriptor rather than a live server. If TensorFlow publishes an official server, this page will update to it on the next build.
Descriptor
Candidate descriptor · transport http
Tools
get_model_status— Get the status of a model in the ModelServer.get_model_version_status— Get the status of a specific model version.get_model_label_status— Get the status of a model version identified by label.get_model_metadata— Get the metadata (signature definitions) of a model.get_model_version_metadata— Get the metadata for a specific model version.classify_model— Run classification inference using the specified model.classify_model_version— Run classification inference using a specific model version.regress_model— Run regression inference using the specified model.regress_model_version— Run regression inference using a specific model version.predict_model— Run prediction inference using the specified model.predict_model_version— Run prediction inference using a specific model version.
About MCP
The Model Context Protocol (MCP) is an open protocol Anthropic introduced for connecting LLM-based agents to external tools and data sources. Providers publish MCP servers that expose their API surface as structured, discoverable tools — an MCP-compatible client (Claude Desktop, Cursor, Cline, Continue, etc.) can connect to the server and call its tools without any per-provider integration code.
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