Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful detail about what the returned state includes (installed MCPs, connection status, associated accounts, catalog tool counts), going beyond a generic 'returns state' statement. It does not reveal any side effects or limitations, but for a read-only info tool this is sufficient.
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 a single, well-structured sentence that front-loads the core purpose ('Returns the current toolkit state') and then lists the specific data elements. Every word contributes meaning; there is no repetition or filler.
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?
For a no-parameter, read-only informational tool with strong annotations, the description fully conveys what the tool returns. The enumerated list of state components (installed MCPs, connection status, accounts, catalog tool counts) gives the agent a complete picture without needing an output schema.
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 zero parameters, and the schema is empty. The description therefore doesn't need to explain any inputs, and the baseline of 4 is appropriate because there is nothing to document.
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 uses a specific verb ('Returns') and clearly defines the resource ('current toolkit state'), enumerating its contents: installed MCPs, connection status, accounts, and catalog tool counts. This unambiguously distinguishes it from sibling tools that focus on specific financial operations or authentication.
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 provides clear context that this tool is for retrieving an overview of integrated MCPs and their status. It does not explicitly name alternatives or state when-not-to-use it, but the purpose is so distinct from the sibling tools that the appropriate usage is easily inferred.
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.
Most tools have clearly distinct purposes, especially within the openfinance_* group (list vs get vs sync vs status). A few potential overlaps exist (e.g., openfinance_list_transactions vs openfinance_list_transactions_by_item, openfinance_get_account_balance vs openfinance_list_accounts), but descriptions are detailed enough to guide correct selection.
The openfinance_* tools follow a consistent verb_noun pattern (e.g., openfinance_list_accounts, openfinance_get_item_status). However, non-openfinance tools (authenticate, connect, marketplace, toolkit_info) use a different style, and one tool (openfinance_list_transactions_by_item) breaks the pattern slightly. Overall readable and predictable within the primary domain.
With 25 tools, the count is on the heavy side per the calibration rubric (16-25 feels heavy). The server covers a broad financial data domain, which justifies the number, but it may present a steep learning curve and potential overwhelm for agents.
The tool surface is comprehensive for read-only Open Finance data access: accounts, transactions, balances, bills, loans, investments, category management, connection lifecycle, and status monitoring. Minor gaps exist (e.g., no direct payment initiation, no investment transaction creation), but for the stated purpose of data and analysis, coverage is strong.