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contextium-mcp-server

contextium-mcp-server

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by contextium-io
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suggest_libraries

Suggest relevant context libraries to attach to a new workflow by comparing keyword overlap. Call this before create_workflow to let users select matching libraries.

Instructions

Suggest existing context libraries that look relevant to a workflow you are about to create, ranked by keyword overlap between the workflow name/description and each library's name/description. Call this BEFORE create_workflow (or create type=workflow) so you can present the matches to the user and let them choose which to attach via projectIds. Nothing is auto-attached — these are suggestions only. Returns [] when no libraries score above zero.

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": "suggest_libraries"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesThe name of the workflow being created.
descriptionNoThe workflow description, if any — improves match quality.
workspaceIdNoWorkspace ID. If not provided, uses your default workspace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Describes ranking method (keyword overlap), return behavior ([] when no matches), and that it's suggestions only. No annotations provided, so description fully covers behavioral aspects.

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?

Concise two-sentence description that front-loads purpose, includes usage guidance and return behavior without unnecessary detail.

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?

No output schema, but description states return value ('[]' when none). Parameter count 3, all explained with usage context. Sibling tools are many but description provides clear usage context.

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 100% (baseline 3). Description adds context: 'name' is workflow name, 'description' improves match quality, 'workspaceId' defaults if omitted. This adds value beyond the schema.

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 the tool suggests relevant context libraries based on keyword overlap, and distinguishes it from siblings by specifying it's for use before creating a workflow and that nothing is auto-attached.

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

Usage Guidelines5/5

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

Explicit guidance to call before create_workflow, explains that results are suggestions for user selection, and states that nothing is auto-attached.

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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