mcp-server

Generate a text embedding

forcedream_generate_embedding

Read-only

Generate a real 1024-dim vector embedding for text via Voyage voyage-3.5, retrieval-optimised. Returns the vector, dimensions, token count, WORM-sealed. Requires authentication (per-token charge).

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": {
      "text": "<text>"
    },
    "name": "forcedream_generate_embedding"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes	Text to embed (max ~32000 chars).
`input_type`	No	Optional: "query" or "document".

Output Schema

Name	Required	Description	Default
`tokens`	No
`embedding`	Yes
`worm_seal`	No
`cost_pence`	No
`dimensions`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedJul 12, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Adds context beyond annotations: returns vector, dimensions, token count, WORM-sealed, and per-token charge. No contradiction with annotations.

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?

Three sentences, front-loaded with key verb-resource and model details, no wasted words.

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?

Given output schema exists, description sufficiently covers purpose, parameters, behavior, cost, and immutability for a simple embedding tool.

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

Parameters3/5

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

Schema coverage is 100% and description essentially repeats schema info without adding new meaning beyond what's already in parameter descriptions.

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?

Description clearly states 'Generate a real 1024-dim vector embedding for text' with specific model and optimization, distinguishing it from sibling tools that handle other tasks.

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

Usage Guidelines3/5

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

Implies usage for embedding tasks and mentions authentication and per-token charge, but does not explicitly state when to use versus alternatives or when not to use.

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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