Returns connection status and URLs. When all providers are connected, returns authenticated:true and empty pending[]. When credentials are missing, returns connect_url for the toolkit and per-install URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, which already disclose safe read-only behavior. The description adds context about state transitions: when credentials are missing vs when all connected, explaining the returned structures. This exceeds what annotations provide and adds value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) with key information front-loaded: what it does and expected outputs. It's efficient without unnecessary fluff. Minor deduction for not explicitly delineating edge cases, but it's well structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 params) and output schema absence, the description covers the essential states. However, it could mention potential errors (e.g., partial connection, network issues) or what 'pending' means more explicitly. It's adequate but leaves minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema coverage is 100% (vacuously). No parameter semantics needed. The description focuses on output semantics, which is beneficial. Since there are no parameters, baseline 4 applies as the description doesn't need to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Returns connection status and URLs' with specific details about authenticated state and pending array. While it doesn't explicitly name sibling tools, the context of an authentication toolset makes its purpose distinct: checking connectivity rather than performing authentication. It's specific enough to differentiate from the 'authenticate' sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking connection status without stating when to use it versus alternative tools. It doesn't explicitly say 'use this to check if all providers are connected before other operations' or mention when not to use it. Context signals show parameters 0, so usage is implied but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tool names themselves are distinct (e.g., guru_subscriptions_get vs guru_subscriptions_activities), but the descriptions for each resource are identical except for a '[Flattened action: X]' tag, listing all possible actions. This repetition can confuse agents into selecting the wrong tool, especially since many tools share the same description body. The naming is clear but the descriptive overlap undermines disambiguation.
The majority of tools follow a consistent pattern: guru_<resource>_<action> for reads and guru_<resource>_write_<action> for writes. However, there are outliers like 'authenticate', 'connect', 'marketplace', 'report_bug', etc., which break the pattern. Within the Guru API itself, the naming is highly predictable, but the occasional non-Guru tool reduces overall consistency.
With 101 tools, the server is grossly over-scoped. The API has been fragmented into a separate tool for every action across many resources (e.g., subscriptions alone have 15+ tools). This is far beyond the typical MCP server size and makes the tool list overwhelming and impractical for agents to navigate. The extreme granularity offers no benefit over a smaller, well-organized set.
The tool set covers a wide range of operations: CRUD for contacts, subscriptions, transactions, products, coupons, webhooks, and more, including write actions like refunds, chargebacks, and subscription modifications. The domain appears well-covered, though some resources lack create operations (e.g., no create subscription) and there are a few gaps like missing explicit update for transactions. Overall, the coverage is thorough for the stated API surface.