Skip to main content
Glama
AlgoChains

AlgoChains MCP Server

Official
by AlgoChains

onyx_ask

Read-onlyIdempotent

Ask a natural language question against the Onyx knowledge base with RAG grounding. Returns an answer with cited sources.

Instructions

Ask a natural language question against the Onyx knowledge base with RAG grounding. Returns an answer with cited sources. E.g. 'What is the best CL swing setup in trending regimes?' or 'How do I configure Token Guardian?'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYes
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds that the tool uses RAG grounding and returns cited sources, providing useful context beyond the 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?

The description is extremely concise: two sentences plus examples. Every sentence adds value, and the key action is front-loaded.

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?

For a simple Q&A tool with one parameter and good annotation coverage, the description is mostly complete. It explains the core functionality and output type. Missing details like return format are partially covered by 'answer with cited sources'.

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 0% description coverage for the single parameter. The description enhances understanding by stating that the parameter should be a natural language question and giving examples, which compensates for the lack of schema description.

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

Purpose4/5

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

The description clearly states the tool asks natural language questions against the Onyx knowledge base with RAG grounding and returns answers with cited sources. However, there is a sibling tool 'onyx_search' which may have overlapping functionality, and no explicit differentiation is provided.

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 provides two concrete examples, implying typical usage scenarios. However, it does not specify when to avoid using this tool or mention alternatives (e.g., onyx_search for different query types).

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AlgoChains/algochains-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server