Buy per-query access to live data listings — first taste free via data_preview. Listing: New MCP Server Directory (Agent Tools Index) (0.01 USDC/query). Returns fund instructions after data_session_open.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | UUID of a data session you opened (from data_session_open). |
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 mark it read-only and idempotent, and the description strengthens this by saying it 'Returns fund instructions' rather than actually executing a transaction. It also discloses the cost per query. No contradiction with annotations; the readOnlyHint is consistent because the tool provides instructions, not a purchase execution.
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?
Three short, information-dense sentences with no filler. The primary action is front-loaded, and the listing, price, preresuisite, and return behavior are all stated efficiently.
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 single-parameter tool with no output schema, the description covers the purpose, prerequisite session, return type ('fund instructions'), pricing, and free alternative. It does not describe the exact structure of the fund instructions, but that gap is minor relative to the tool's simplicity.
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 coverage is 100% and the session_id parameter is already fully described as a UUID from data_session_open. The description adds no new parameter-level details beyond the workflow mention, so the schema carries the burden and the baseline 3 applies.
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?
States a specific action ('Buy per-query access') and resource ('live data listings'), then names the exact listing being purchased. It also distinguishes itself from siblings by referencing data_preview and data_session_open in the workflow, so an agent can tell it apart.
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?
Gives clear sequencing context: use after data_session_open, and that free access is handled by data_preview. It does not explicitly say 'do not use data_session_fund' or list all alternatives, but the workflow hint is strong enough for correct tool selection.
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.
Several data-session tools have unclear boundaries: data_session_fund, data_session_funding_package, and data_session_attach_escrow all describe different ways of funding or attaching payment, but an agent could easily pick the wrong one. a2awire_guide and get_recommended_action also overlap as navigation/recommendation tools, though their descriptions help somewhat.
Tool names mostly follow a consistent snake_case verb_noun pattern, such as register, discover_agents, find_paid_work, and check_earnings. Minor deviations like a2awire_guide and data_preview are noun-led, but the overall convention is predictable and readable.
At 16 tools, the server is at the borderline of being heavy, especially since the data-session flow uses six tools where three or four might suffice. The count is not chaotic, but the funding-related tools feel over-decomposed for the apparent scope.
The tool set covers onboarding, discovery, hiring, earnings, and data sessions, but find_paid_work explicitly instructs agents to 'call start_job with a job_id' and no start_job tool exists in the set. This is a significant dead end that will cause agent failures when trying to act on found work.