Skip to main content
Glama
Sign In

Galatic.ai

by ai.galatic
OverviewDiscussionsAdmin

Fetch library item

fetch
Read-onlyIdempotent

Get one of the user's library items by id (from search or list_gallery) as { id, title, text, url, metadata }. title is the item title or prompt; text is its prompt or description; url always links the gallery page, not the file; metadata is the full item, whose contentUrl and thumbnailUrl are signed, playable links. Read-only; 404 for an item that is not the caller's. Use search to find items by text.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "fetch"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYes
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
conversation_idNoPass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations with genuinely useful behavior: a 404 is returned for items not owned by the caller, and the returned url points at the gallery page rather than the file, while metadata.contentUrl and thumbnailUrl are signed, playable links. For a tool with no output schema, that disclosure is exactly what an agent needs to interpret results without being surprised.

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

Conciseness4/5

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

Front-loads the action and scope in the first clause, then attaches field-level clarifications that each earn their place; nothing is repeated from the schema or annotations. It is dense to the point of being a single run-on sentence with many semicolon clauses, which costs a little readability.

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?

With no output schema, the description assumes responsibility for return values and does so field by field (id, title, text, url, metadata plus the signed sub-links), and it covers the main failure mode (404 for non-ownership). Nothing an agent needs in order to call this correctly or interpret the response 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 coverage is 75%, and the one undocumented property, id, is given real semantics by the description ("by id (from search or list_gallery)"), telling the agent where a valid value comes from. The context and llm_model plumbing parameters carry their own schema descriptions, so nothing important is left unexplained.

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 ("Get one of the user's library items by id") plus the scope of the caller's own library, and distinguishes it from siblings by naming search and list_gallery as the id sources. The return shape is spelled out inline, so an agent knows exactly what it gets back.

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

Usage Guidelines4/5

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

Explicitly routes the agent: ids come from search or list_gallery, and "Use search to find items by text" marks the boundary against the sibling that does text lookup. It stops short of stating when-not-to-use conditions such as bulk retrieval or non-id lookups, but the primary routing decision is clear.

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

All Galatic.ai toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources