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Glama

Oi

by io.github.carhaix

Who Am I

oi.auth.whoami
Read-onlyIdempotent

Return the current Oi MCP authentication, organization context, billing plan, current limits, and billing link for debugging. Use this when the user asks who Oi is authenticated as, which organization this MCP session is using, what plan or limits apply, or why Codex/ChatGPT may be seeing different Oi data. Does not return access tokens, refresh tokens, or secrets.

Plan and Billing

Current organization plan: Business. Current limits: 10,000 seats; 10,000 private Guardrails; 10,000 private Skills; 10,000 private Contexts; 10,000 private Workflows; 10,000 Connections; 10,000 API keys; 1,000,000 Agent messages per day; 1,000,000 Agent messages per month. Billing and upgrades: https://app.oioioi.ai/dashboard/organization/billing. When a user asks for work that exceeds the current plan or an unavailable paid capability, do the portion available on the current plan, clearly say what is blocked by the plan, and include the billing link for upgrading. Do not invent exceptions, temporary limit increases, prices, or hidden capabilities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNo
scopeNo
userIdYes
runtimeNo
apiKeyIdNo
authTypeYes
providerNo
sessionIdNo
billingPlanNo
organizationIdNo
organizationNameNo
organizationAccessYes
organizationAccessErrorNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false), the description adds a safety guarantee: 'Does not return access tokens, refresh tokens, or secrets.' It also states the current plan, exact limits, and a directive on what to do when work exceeds the plan, providing rich behavioral context for the agent.

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?

The core purpose, use cases, and security note are front-loaded, followed by a structured '## Plan and Billing' section. It is somewhat verbose with a long list of static limits that could go stale, but the section is organized and relevant to the tool's purpose.

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?

For a zero-parameter read-only introspection tool with an output schema, the description covers purpose, triggering conditions, security exclusions, plan/limit context, and the billing link. Nothing needed for an agent to call it correctly is missing.

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 zero parameters and 100% schema description coverage, so no parameter semantics are needed. Per the baseline rule for 0-param tools, a 4 is appropriate; the description adds no param-specific detail because none exists.

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 opens with a specific verb and resource: 'Return the current Oi MCP authentication, organization context, billing plan, current limits, and billing link for debugging.' This both states an exact action and scopes the tool to a unique resource, clearly distinguishing it from the many sibling tools focused on skills, guardrails, or contexts.

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?

It explicitly enumerates triggering user intents: 'who Oi is authenticated as, which organization this MCP session is using, what plan or limits apply, or why Codex/ChatGPT may be seeing different Oi data.' This gives an agent concrete conditions for selection without needing to infer from the name or title.

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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TDQS

A3.5/5.0
Disambiguation4/5

Resource prefixes (contexts, skills, guardrails, workflows, connections) make most tools clearly distinct, and parallel lifecycle verbs are scoped by resource name. The main ambiguity is within the guardrails publish/release/unpublish lifecycle and between brain.save-feedback, contexts.save-draft-feedback, and the two report tools, though detailed descriptions mostly resolve it.

Naming Consistency4/5

Tools overwhelmingly follow an oi.<resource>.<verb> snake_case pattern, with create/get/list/update/use repeated consistently across resource types. Deviations include resource-less oi.recommend, noun-style oi.auth.whoami, and inconsistent release handling (separate guardrails.release vs action=release on contexts/skills update).

Tool Count2/5

38 tools is too many for a single server, mainly because the same lifecycle pattern is repeated across Contexts, Skills, Guardrails, and Workflows. Each tool may be individually justifiable, but the set feels bloated and could benefit from consolidation or splitting into per-resource servers.

Completeness3/5

CRUD coverage is uneven: Guardrails have create/update/delete/list/get plus publish/unpublish/release, while Contexts, Skills, and Workflows lack any delete or archive tool, and Brain has only save-feedback with no read/update/delete path. Connections and auth are read/use-only, which may be intentional but leaves management actions absent.

Resources