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Glama

ToolRouter

Add Connector

connector_add

Connect a new OAuth account or MCP server. For OAuth: pass type: "oauth", kind: "slack". For MCP catalog: pass catalog_slug. For custom MCP: pass url + auth_type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoMCP server endpoint URL (custom MCP).
kindNoOAuth connector kind (e.g. "slack", "notion"). Required for type: "oauth".
slugNoShort identifier for the connection.
typeNoType of connector to add.
billingNoScope: "personal" (default), "team" (auto-resolves), a team slug, or "team:<id>".
auth_typeNoAuth type (custom MCP). Default: none.
auth_tokenNoAuth token or API key.
header_nameNoCustom header name (for header_key auth).
catalog_slugNoMCP catalog slug for one-click connect.
display_nameNoHuman-readable name (custom MCP).

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations indicate this is a mutating, non-idempotent action, and the description's 'Connect a new...' phrasing confirms it creates persistent state. However, it does not disclose side effects such as whether an OAuth consent flow is triggered, whether duplicate connections are rejected or replaced, or how auth tokens are stored. The description adds some value beyond the annotations but leaves behavioral details underexplained.

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?

Three short sentences with no filler. The main action is front-loaded, and the mode-specific guidance is compact and easy to scan. Every sentence earns its place.

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

Completeness3/5

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

For a 10-parameter tool with no output schema and no required parameters, the description provides useful mode routing but does not state the required parameter combinations as strict constraints, nor does it describe the return value or expected outcome after a successful add. An agent would benefit from knowing what happens after calling this tool, such as whether a connector ID is returned or how to verify success via connector_list.

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 description coverage is 100%, so the baseline is 3. The description adds value by grouping parameters into three usage modes and naming the key combos: type+kind, catalog_slug, and url+auth_type. It does not discuss every parameter like billing or header_name, but those are already well-documented in 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?

The description names a specific action and resource: 'Connect a new OAuth account or MCP server.' It then enumerates the three supported modes (OAuth, MCP catalog, custom MCP), making the tool's scope immediately clear and distinguishing it from sibling tools like connector_list and connector_remove.

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?

The description gives explicit condition-to-parameter guidance: 'For OAuth: pass type: "oauth", kind: "slack". For MCP catalog: pass catalog_slug. For custom MCP: pass url + auth_type.' This tells the agent exactly how to invoke the tool in each scenario. It does not name alternative sibling tools for exclusion, but the usage context for adding a connector is clear.

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

B3.4/5.0
Disambiguation4/5

Tools are grouped by clear resource prefixes (account_, brain_, connector_, credential_, file_, job_, key_), and most actions have distinct purposes. A few boundaries overlap—brain_admin's lint action duplicates brain_lint, and account_preferences/setup/switch could momentarily confuse—but the descriptions resolve most ambiguity.

Naming Consistency3/5

The dominant pattern is resource_verb for actions (file_read, job_cancel, key_create) and resource_noun for state views (credits_balance, brain_settings, account_preferences), which is readable. However, exceptions like discover, use_tool, top_up_credits, and feedback_request_tool break the pattern, and the set is not consistently verb_noun.

Tool Count2/5

47 tools is well beyond the comfortable range; even though prefixes organize them, the agent faces a large selection surface with many narrowly scoped tools. A more consolidated set with action-based subcommands would be easier to navigate.

Completeness4/5

Core workflows are covered end-to-end: account setup and billing, connector and credential management, file CRUD, job polling, key lifecycle, brain knowledge management, and catalogue discovery/execution. Gaps are minor—outfit/persona/product/scene are list-only, connectors lack an update operation, and there is no explicit single-page brain get—but agents can generally work around them.