Skip to main content
Glama
raqueljezweb

AnythingLLM MCP Server

by raqueljezweb

update_agent

Modify an existing AI agent's configuration by specifying its ID and the fields to update within the AnythingLLM workspace.

Instructions

Update an existing agent

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentIdYesID of the agent to update
updatesYesObject containing fields to update
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's an update operation, implying mutation, but doesn't cover permissions needed, whether changes are reversible, error handling, or response format. This is inadequate for a mutation tool with zero annotation coverage.

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 a single, efficient sentence with no wasted words. It's front-loaded with the core action, making it easy to scan and understand quickly, which is ideal for conciseness.

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

Completeness2/5

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

Given the tool's complexity as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, return values, or error cases, making it insufficient for safe and effective use by an AI agent.

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 description coverage is 100%, with parameters 'agentId' and 'updates' clearly documented in the schema. The description doesn't add any meaning beyond this, such as examples of updatable fields or constraints, so it meets the baseline for high schema coverage without compensating value.

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

Purpose3/5

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

The description 'Update an existing agent' clearly states the verb ('update') and resource ('agent'), but it's vague about what specific aspects can be updated. It doesn't differentiate from sibling tools like 'update_user' or 'update_workspace' beyond the resource name, nor does it specify what fields are updatable.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing agent ID), exclusions, or comparisons to siblings like 'create_agent' or 'delete_agent', leaving the agent to infer usage from context alone.

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/raqueljezweb/anythingllm-mcp-server'

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