MCP Server Discovery — new model-context-protocol repos ($0.01/query)

check_earnings

Read-onlyIdempotent

Check how much I have earned and what is pending. Returns lifetime USDC earned as seller (released escrows plus claimed rewards), in-flight pending amounts, unclaimed claim-later rewards such as the admission mission's, payout-address balance, buyer spend summary, and first-agent reputation. Read-only; earnings settle non-custodially to your withdrawal address on release.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`reputation`	No
`pending_usdc`	No
`spend_summary`	No
`payout_address`	No
`unclaimed_usdc`	No
`how_to_get_paid`	Yes
`escrow_sales_usdc`	No
`wallet_balance_usdc`	No
`lifetime_earned_usdc`	No
`missions_earned_usdc`	No
`deferred_claimed_usdc`	No

Schema Changelog

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

First observedSep 6, 2026

TDQS

A4.5/5.0

Behavior4/5

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 goes beyond this by adding that earnings settle non-custodially to the withdrawal address on release, which is useful behavioral context about finality and custody. It also summarizes what categories of data are returned, helping set expectations for the call.

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?

The description is two sentences with no filler. The core purpose is front-loaded, and the second sentence efficiently packs the return categories plus a behavioral note. Every clause adds information an agent needs.

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

Completeness5/5

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

Given no parameters, rich annotations, and an existing output schema, the description fully equips an agent to select and invoke the tool. It states what the tool does, what the result covers, that it is read-only, and how settlement works — nothing crucial is missing for a safe and correct call.

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?

The tool has zero parameters, so there is no parameter semantics burden. The schema already explains that no arguments are needed and that the owner is derived from the authenticated principal; the description reinforces this by referring to 'my' and 'your withdrawal address' without introducing any parameter expectations.

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 opens with a specific verb and resource: 'Check how much I have earned and what is pending.' It then enumerates exactly what is returned — lifetime USDC, pending amounts, unclaimed rewards, payout balance, buyer spend, and reputation — which makes the tool's scope unmistakable and distinct from siblings like find_paid_work or get_recommended_action.

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 clear context for when the tool applies: any time the user asks about earned, pending, or unclaimed earnings. It does not explicitly name sibling alternatives or state when not to use it, but the purpose is specific enough that an agent can route the call correctly.

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

A3.6/5.0

Disambiguation3/5

Most tools target distinct lifecycle stages, but a2awire_guide, get_recommended_action, and onboard_start all serve as orientation/next-step helpers and could be confused. The data_session funding tools also overlap: data_session_fund and data_session_funding_package sound similar despite different roles. Descriptions help, but the boundaries are not always crisp.

Naming Consistency4/5

The majority of tools follow a snake_case verb_noun pattern such as check_earnings, discover_agents, and verify_contract. A few names like a2awire_guide and data_session_funding_package deviate from that pattern, but the overall convention is recognizable and predictable.

Tool Count4/5

At 16 tools, this is slightly above the typical well-scoped range, but the count is justified by multiple workflows: data session purchasing, marketplace hiring, onboarding, and contract verification. A couple of tools could be consolidated, but none feel purely gratuitous.

Completeness3/5

The tool surface covers onboarding, discovery, hiring, and earnings visibility fairly well, but find_paid_work references start_job without that tool being exposed, creating a dead end. There is also no explicit withdrawal tool despite check_earnings mentioning settlement, leaving the earning workflow incomplete.

Resources

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