MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
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?
Description explains idempotent behavior (calling with token repeatedly same effect) and notes permanent vs session nature. Annotations show idempotentHint=true, destructiveHint=false, readOnlyHint=false – no contradictions. Adds context about config-based login being non-expiring.
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?
Description is fairly concise and front-loaded with the tool's purpose. Every sentence adds value, though the structure could be slightly clearer (e.g., splitting config vs session). Still, no waste.
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?
Does not describe the return value or output schema, which is missing. For an authentication tool, the response format (e.g., success message, token status) would be helpful. However, it covers the core flow adequately for an agent to invoke.
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?
Schema has 0% description coverage for the single parameter 'token'. Description explains that it's a JWT and that omitting it returns a login link, adding essential meaning beyond the schema.
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 is for authentication with two methods: permanent config-based and session-based token paste. It specifies the verb 'authenticate' and the resource (MCP.AI for IDE agents). Siblings like 'connect' do not overlap in purpose.
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?
Provides clear guidance on when to use each method (permanent vs session), including calling with no args to get a link. Does not explicitly compare to siblings, but the context is sufficiently directed for an agent.
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 openfinance_* tools target distinct resources and actions, but several overlap in purpose: list_transactions vs list_transactions_by_item, get_credit_card_bill vs list_credit_card_bills, and multiple connection/status tools expose reconnect URLs. The long descriptions help, but the boundaries are not always immediately obvious.
The openfinance_* tools follow a consistent list_/get_ verb_noun pattern and share a clear prefix. The smaller platform cluster is less consistent — marketplace, connect, authenticate, show_version, toolkit_info — mixing nouns, bare verbs, and snake_case, but it is a minor deviation overall.
At 25 tools, this sits at the heavy end of acceptable. The Open Finance surface is broad enough to justify many of them, but there is redundancy (e.g. list_transactions_by_item largely wraps list_transactions plus account resolution) and a separate platform-management cluster that makes the set feel sprawling.
The Open Finance domain is well covered: connection lifecycle, accounts, balances, transactions, credit-card bills, loans, investments, categories, and provider status are all present, and data flows connect properly between tools. Minor gaps exist, such as no single-transaction fetch or dedicated prompt-management tools, but the marketplace tool fills those roles.