mistral_embeddingsGenerate text embeddings to convert text into numerical vectors for semantic search, similarity analysis, and clustering.
Generate text embeddings for semantic search and similarity.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | Text(s) to embed | |
| model | No | Model ID | mistral-embed |
| encoding_format | No | Encoding format |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds nothing behavioral beyond that - no note on batching semantics, cost, or that repeated identical input yields identical vectors. With annotations carrying the safety load, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no waste. It is efficient, though borderline under-specified rather than genuinely concise-and-complete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Three simple parameters and no output schema, so the description should tell the agent what comes back (an array of float vectors, one per input string). That return shape is omitted, leaving a real gap for an embeddings consumer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so input, model, and encoding_format are already documented in the schema (including the single-or-array anyOf). The description adds no parameter meaning - e.g., that multiple texts produce multiple vectors - so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (Generate) and resource (text embeddings) plus the typical use case (semantic search and similarity). It's clear what the tool does, but it never distinguishes itself from siblings even though embеdding is a unique capability in this server.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Only an implied usage ('for semantic search and similarity') is given. There is no guidance on when to choose this over chat/completion siblings or on batching many inputs in one call versus many calls.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.