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Hubris

by pw.hubris
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This connector has been deprecated

This connector is a duplicate. Use Hubris instead — same endpoint (https://api.hubris.pw/mcp), but with ownership verified, OAuth, all five tools inspected and a quality score.

Chat completion

chat_complete

Run a chat completion on any model in the Hubris catalogue and get the answer back. Full parity with POST /v1/chat/completions — same request shape, same response shape, including tool calls, structured output and reasoning. Streaming is not available here: MCP tool calls are synchronous, and stream is ignored if you pass it.

This is how you reach a model you cannot reach otherwise — pick an id with models_search, then call it here. Useful for delegating a subtask to a cheaper or a stronger model than the one you are running on.

Chat models that draw (Gemini Image, GPT-5 Image) take modalities ["image","text"]; their pictures come back as image content next to the JSON. Voice answers of audio models need streaming and are available through the HTTP API only.

The call spends real money from the account balance: it is billed per token at the catalogue price, in rubles. balance_get shows what is left.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoBest-effort determinism. Not every model honours it.
stopNoUp to four strings that cut the answer short.
modelYesModel id from the catalogue, vendor included and matched exactly, e.g. "anthropic/claude-sonnet-5". Short names and names with a trailing date are rejected. Use models_search to find one.
toolsNoFunction-calling tools, OpenAI shape. Model must have the "tools" capability.
messagesYesConversation so far, oldest first.
reasoningNoExtended thinking on models with the "reasoning" capability: {effort:"low"|"medium"|"high"}, {max_tokens:N}, or {enabled:false} to turn it off.
max_tokensNoCap on the length of the answer, in tokens.
modalitiesNo["image","text"] on chat models that draw (Gemini Image, GPT-5 Image): the pictures come back as image content.
web_searchNoEnables built-in web search on models whose capabilities include "web_search".
temperatureNoSampling temperature, 0–2. Some newer models reject it; leave it out unless you need it.
tool_choiceNo"auto", "none", "required", or a specific function to force.
response_formatNo{type:"json_object"} or {type:"json_schema", json_schema:{…}} to constrain the answer to JSON.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / modalities
      Added value: +{
+  "description": "[\"image\",\"text\"] on chat models that draw (Gemini Image, GPT-5 Image): the pictures come back as image content.",
+  "items": {
+    "enum": [
+      "text",
+      "image"
+    ],
+    "type": "string"
+  },
+  "type": "array"
+}
  2. Changed16 schema fields changed
    • addedInput schema / properties / max_tokens / description
      Added value: +"Cap on the length of the answer, in tokens."
    • addedInput schema / properties / messages / description
      Added value: +"Conversation so far, oldest first."
    • addedInput schema / properties / messages / items / properties / content / description
      Added value: +"Message text. Can be an array of parts for multimodal input — {type:\"text\"} and {type:\"image_url\"} — on models whose capabilities include \"vision\"."
    • addedInput schema / properties / messages / items / properties / name / description
      Added value: +"Optional author name."
    • addedInput schema / properties / messages / items / properties / role / description
      Added value: +"Who the message is from."
    • addedInput schema / properties / messages / items / properties / tool_call_id / description
      Added value: +"Which tool call this result answers, on a tool message."
    • addedInput schema / properties / messages / items / properties / tool_calls / description
      Added value: +"Tool calls the model asked for, on an assistant message."
    • addedInput schema / properties / model / description
      Added value: +"Model id from the catalogue, vendor included and matched exactly, e.g. \"anthropic/claude-sonnet-5\". Short names and names with a trailing date are rejected. Use models_search to find one."
    • addedInput schema / properties / reasoning / description
      Added value: +"Extended thinking on models with the \"reasoning\" capability: {effort:\"low\"|\"medium\"|\"high\"}, {max_tokens:N}, or {enabled:false} to turn it off."
    • addedInput schema / properties / response_format / description
      Added value: +"{type:\"json_object\"} or {type:\"json_schema\", json_schema:{…}} to constrain the answer to JSON."
    • addedInput schema / properties / seed / description
      Added value: +"Best-effort determinism. Not every model honours it."
    • addedInput schema / properties / stop / description
      Added value: +"Up to four strings that cut the answer short."
    • addedInput schema / properties / temperature / description
      Added value: +"Sampling temperature, 0–2. Some newer models reject it; leave it out unless you need it."
    • addedInput schema / properties / tool_choice / description
      Added value: +"\"auto\", \"none\", \"required\", or a specific function to force."
    • addedInput schema / properties / tools / description
      Added value: +"Function-calling tools, OpenAI shape. Model must have the \"tools\" capability."
    • addedInput schema / properties / web_search / description
      Added value: +"Enables built-in web search on models whose capabilities include \"web_search\"."
  3. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare non-read-only, non-idempotent, open-world behavior, but the description goes well beyond them: it discloses real per-token billing in rubles against the account balance, the synchronous/streaming limitation, capability gating per parameter family, that image models return image content alongside the JSON, and that audio output is HTTP-only. That is exactly the context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose, then layered by concern: parity/limitations, routing, multimodal edge cases, and cost. Four short paragraphs for a 12-parameter tool, with no sentence that could be deleted without losing operative information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a high-complexity, no-output-schema tool, it covers what the response contains (answer plus image content), what streaming does not do, which parameters are capability-gated, and the financial side effect. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3, and the description earns an extra point by explaining how modalities behaves on drawing models and by tying tools/web_search/reasoning parameters to model capability requirements. It does not add syntax detail for the remaining parameters (seed, stop, response_format), but those are already well documented in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Run a chat completion on any model in the Hubris catalogue and get the answer back') and immediately scopes it against the rest of the Hubris surface by invoking the POST /v1/chat/completions parity contract. An agent can distinguish it from embeddings_create, image_generate, or rerank without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent: pick a model id with models_search, check the balance with balance_get, and use the HTTP API when streaming or audio output is required. It also names the alternative use case (delegating to a cheaper or stronger model) and states the negative case ('stream is ignored if you pass it').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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