Skip to main content
Glama

messages-send

messages-send

Send a direct message to another user, stored as a case file item in their inbox. Returns the message ID.

Instructions

Sends a direct message to another user. Stored as a CaseFileItem of type 'message' in the recipient's inbox case (or a specified context case). Returns the message_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesMessage body. Markdown is allowed; rendered by clients that support it.
context_case_idNoOptional case to attach the message to. Defaults to the recipient's personal Inbox case (preferences.inbox_case_id).
priorityNoDelivery priority: "normal" (default) or "urgent"
reply_to_message_idNoOptional message RID this message is replying to. Enables threading — orchestrators can correlate replies with their originating requests via messages-list(reply_to_message_id: ...).
subjectNoOptional subject line
to_agent_idNoOptional specific recipient AgentSession RID. When set, the dispatcher targets only that agent.
to_emailNoRecipient email address; resolved to a user RID server-side.
to_machine_idNoOptional machine identifier. Resolved to the recipient's first online agent on that machine. Falls back to broadcast if no online agent matches.
to_user_idNoRecipient user RID. Provide this OR to_email — one of the two is required.
Behavior3/5

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

With no annotations provided, the description discloses storage behavior and threading but omits details like authentication requirements, rate limits, or error handling for missing recipients.

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 short, front-loaded with the main action, and every sentence adds value. No redundant phrases.

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?

The description covers the main action, return value, and storage context. Given no output schema, it adequately explains the basics, but lacks details on error conditions or behavioral nuances.

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?

All 9 parameters have descriptions in the schema (100% coverage), so the description adds limited extra meaning beyond reiterating schema info. The mention of threading for reply_to_message_id provides marginal value.

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 tool sends a direct message to another user, mentioning storage as a CaseFileItem and return of message_id. It distinguishes itself from sibling tools like messages-broadcast and messages-list.

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 context about threading and storage but does not explicitly state when to use this tool over alternatives like messages-broadcast. Usage guidance is implied but lacks clear exclusions.

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/mstang/casemgr-mcp'

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