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Redis MCP Server

Redis MCP Server

by Yuchenhui
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_vector_from_hash

Retrieve a vector stored as a binary blob in a Redis hash and convert it back to a list of floats.

Instructions

Retrieve a vector from a Redis hash and convert it back from binary blob.

Args: name: The Redis hash key. vector_field: The field name inside the hash. Unless specifically required, use the default field name

Returns: The vector as a list of floats, or an error message if retrieval fails.

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": {
      "name": "<name>"
    },
    "name": "get_vector_from_hash"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
vector_fieldNovector

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.5

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description must shoulder the burden. It mentions the retrieval, conversion from binary blob, and error returns, but omits important behaviors like what happens if the key does not exist or if the field is missing. The transparency is adequate but not thorough.

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?

The description is extremely concise, with clear sections for Args and Returns. Every sentence serves a purpose: stating the main action, explaining parameters, and describing the return value. No unnecessary information is present.

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

Completeness4/5

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

Given the simplicity of the tool (2 parameters, no output schema), the description covers the main aspects: retrieval, conversion, parameter explanations, and return value. Minor gaps exist (e.g., no mention of key existence requirements), but overall it is sufficient for a basic retrieval tool.

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?

The input schema has no parameter descriptions (0% coverage), so the description compensates by explaining the meaning of 'name' (Redis hash key) and 'vector_field' (field name with default usage guidance). This adds significant value beyond the schema's type and default, earning a high score.

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?

The description clearly states the action ('Retrieve a vector') and the resource ('from a Redis hash and convert it back from binary blob'). The sibling tool 'set_vector_in_hash' is the opposite operation, making the purpose distinct. The verb and resource are specific, earning a top score.

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?

The description lacks explicit guidance on when to use this tool versus alternatives. While the sibling 'set_vector_in_hash' implies this is the read counterpart, no direct comparison or exclusion criteria are provided. The default field name is noted, but no context for choosing different fields is given.

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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