LM-Kit One · Compatibility

The coverage matrix, stated.

What each API dialect serves, endpoint by endpoint, including what is missing. A stated limitation beats a discovered one.

OpenAI · Anthropic · Ollama MCP · native REST One engine behind all of them

OpenAI dialect.

Deep enough that OpenAI-shaped retrieval and agentic flows run against a private deployment, not only single chat turns.

EndpointStatusNotes
Inference
POST /v1/chat/completions Served Streaming, tools, vision content, structured output; parameters below
POST /v1/completions Served Legacy completions, with per-token logprobs and alternatives on request
POST /v1/embeddings Served Any embedding-capable model in the catalog
GET /v1/models, GET /v1/models/{id} Served The list envelope OpenAI SDKs parse; the Anthropic shape when the request carries anthropic-version
Files and retrieval
/v1/files upload, list, retrieve, delete Served Scoped to the calling key; purpose is recorded and filters the list
/v1/vector_stores create, list, get, delete Served Backed by the built-in search engine
/v1/vector_stores/{id}/files attach, list, retrieve, detach Served Status moves from in_progress to completed as the embedding pass lands, so SDK create-and-poll helpers work
Responses API
POST /v1/responses Served Create; retrieve, delete and input items below
GET /v1/responses/{id}, GET .../input_items, DELETE Served Stored responses round-trip
POST /v1/responses/{id}/cancel Not served Background execution is refused by name, so there is nothing to cancel

Chat parameters: honored, extended, or ignored.

Compatibility claims usually die on parameters, so here is the split for /v1/chat/completions.

ParametersStatusNotes
temperature, top_p, max_tokens / max_completion_tokens, stop, seed, frequency_penalty, presence_penalty, logit_bias Honored Mapped onto the engine's sampling controls
stream, stream_options Honored Server-sent events, with usage in the final chunk
response_format (json_object, json_schema) Enforced Grammar-constrained decoding: the completion parses, or the request is refused up front with an OpenAI-shaped error
tools, tool_choice Honored Exercised end to end by real agentic clients
logprobs, top_logprobs Honored Per-token log probabilities with up to 20 alternatives per position
agent, skill, server_tools, memory, reasoning_effort, thinking LM-Kit extensions Adopt a named server-side agent, pin a skill, enable governed server tools and persistent memory, set thinking effort
Legacy functions, function_call Refused by name A 400 points at tools; the deprecated shape is never approximated
parallel_tool_calls, and wire-compatibility fields such as service_tier, audio, prediction Accepted, ignored Parsed so clients do not break; no engine equivalent yet

Anthropic dialect.

The Messages shape, so SDKs and coding agents built on it keep working while inference stays inside your network.

EndpointStatusNotes
POST /v1/messages Served Streaming, system, tools and tool_choice, stop_sequences, temperature / top_p / top_k, and thinking with a token budget
GET /v1/models, GET /v1/models/{id} Served The Anthropic shape, paged, selected by the anthropic-version header every SDK sends
POST /v1/messages/count_tokens Served Exact from the model's own tokenizer when the model is resident, estimated otherwise: a count never costs a model load

Ollama dialect.

The whole surface, lifecycle included, which is the part shims normally skip: the stock CLI drives this server unmodified.

EndpointStatusNotes
/api/chat, /api/generate Served Streaming and non-streaming
/api/embed, /api/embeddings Served Current and legacy embedding shapes
/api/tags, /api/show, /api/ps, /api/version Served Discovery and status
/api/pull, /api/create, /api/copy, /api/delete Served Model lifecycle against this server's catalog and store
/api/blobs/{digest} (HEAD, POST) Served A multi-gigabyte model upload is a tested path
/api/push Not served By design: this server is not a model registry, and the endpoint says so instead of pretending

MCP and the native surface.

The dialects are the on-ramp. The native REST API is the whole server, and MCP is how assistants reach a governed slice of it.

MCP

One endpoint, a curated catalog

An MCP endpoint at /mcp exposes document and knowledge tools to assistants. Which tools are reachable is an operator decision, not a client one.

Native REST

Over a hundred endpoints

Documents, extraction, search, agents, PDF operations, training and model management: operations no general chat API models. The server ships its own API reference.

Anything not listed on this page is not served. The matrix is maintained with each release; if a client you depend on needs an endpoint marked missing, tell us.

LM-Kit One

Point a client you already own at it.