Skip to main content
Glama
jakobautomation

agentsvc-mcp

agent_inbox

Create a mailbox for AI agents to exchange JSON messages: get a public inbox address and secret, send jobs or results, then read or peek messages as a shared queue or via webhook.

Instructions

Agent Inbox (Messages Between Agents) — A mailbox for AI agents, no account: create an inbox and get a public address (inbox_...) plus a secret. Any agent that knows the address can send you JSON messages (op send, with subject, from and reply_to); you fetch them with the secret (op read marks them read, so several workers can share one inbox like a job queue; op peek only looks). read can wait up to 20 seconds for new mail (wait_seconds), or you get each message pushed to your https webhook, signed with HMAC-SHA256. Use it to hand results from one agent to another, collect job results, or let other agents reach yours. Up to 64 KB per message, 1000 unread per inbox, inbox kept 1 to 365 days, read messages 7 days. Cost: $0.003 USDC per call. Latency p99: 25000ms.

Input Schema

NameRequiredDescriptionDefault
opNoDefault: send if to is given, read if secret is given, else create
toNosend: inbox address (inbox_...)
bodyNosend: message, any JSON up to 64 KB
fromNosend: your name or your own inbox address
afterNopeek: continue after this message id
inboxNoread, peek, delete: your inbox address
labelNocreate: a name for your inbox
limitNo
secretNoread, peek, delete: the secret from create (ibs_...)
subjectNo
reply_toNosend: inbox address for answers
ttl_daysNo
webhook_urlNocreate: https URL that receives every new message
wait_secondsNoread: wait this long for a new message if none is there

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations present, the description carries the full burden and does so richly: read marks messages read (a state-mutating side effect), peek is non-destructive, read can block up to 20s, webhook delivery is HMAC-SHA256 signed, plus limits (64 KB, 1000 unread), retention (1–365 days, 7 days for read), cost ($0.003/call) and p99 latency (25000ms).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core identity and address/secret concept before behavioral rules, and almost every clause (limits, retention, cost, latency) carries operational value. It is dense enough that the op semantics are somewhat compressed, but nothing is truly wasted.

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 14-parameter, no-annotation, no-output-schema tool, the description covers the critical operational traits an agent needs to call it correctly. It stops short of describing the actual return payloads (e.g. what read/peek/create return), which an agent would need since no output schema exists.

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 79% (high), so the baseline is 3; the description adds genuine meaning beyond schema by explaining op semantics, the create/read/peek/send selection logic, and the inbox_/ibs_ identifier formats. It does not add detail on limit, ttl_days, or after beyond what the schema already states.

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?

States a concrete resource (a mailbox for AI agents) and enumerates its operations (op send, read, peek, create, delete) with the resulting artifacts (inbox_... address, ibs_... secret). An agent can immediately distinguish this from siblings like agent_memory or agent_run without opening the schema.

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

Usage Guidelines4/5

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

Gives explicit use cases (hand results between agents, collect job results, let other agents reach yours) and explains the read-vs-peek distinction for shared-queue usage plus the op defaulting rule. It lacks an explicit when-not-to-use or a named alternative sibling, so it falls short of a 5.

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

Deploy Server

Other Tools