Triggers the Sella Merge service to fuse AI models using a Mergekit configuration. Returns a Job ID to track progress. Requires an x402 payment signature covering $15 USDC for compute.
| Name | Required | Description | Default |
|---|---|---|---|
| config_yaml | Yes | The valid Mergekit configuration in YAML format. | |
| payment_signature | No | Base64 x402 PAYMENT-SIGNATURE header value (v2 preferred). |
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 indicate destructiveHint=true, and the description adds that the tool triggers a service and returns a Job ID. It also discloses the payment requirement and cost, providing behavioral context beyond annotations.
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?
Two sentences that efficiently convey purpose, payment requirement, and output type. No unnecessary words, but could be slightly more structured with a clear output statement.
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 has only 2 parameters and no output schema, the description covers purpose, payment, and tracking (Job ID). It does not mention any rate limits or error states, but for a straightforward API call this is sufficient.
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%, so both parameters are documented. The description adds that config_yaml must be valid Mergekit YAML and that the payment signature should use v2 preferred, which adds meaning beyond the schema's base descriptions.
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?
Clearly states it triggers the Sella Merge service to fuse AI models using Mergekit configuration, and returns a Job ID. This is a specific verb-resource pair that distinguishes it from siblings which include dataset and business operations.
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?
Explicitly mentions the requirement for an x402 payment signature covering $15 USDC, which informs when to use this tool (i.e., when payment is available). Does not explicitly state when not to use or provide alternatives, but the context of model merging is clear.
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, but the deprecated tools (list_datasets, list_market_apis, search_datasets, try_dataset) overlap with modern replacements (search_catalog, get_listing). Some functional overlap exists between get_activity and charge_list, but descriptions clarify their scopes. Overall, an agent can usually tell tools apart, with a few legacy remnants.
Tool names follow a consistent snake_case verb_noun pattern (browse_catalog, business_start, charge_create, etc.). Even the deprecated tools adhere to the same style. There are no mixed conventions or vague verbs like 'process' or 'run'. The naming is highly predictable.
At 52 tools, this is a large surface. The domain is broad (marketplace buying/selling, business management, policy, storefront, distribution, authentication), so many tools are justifiable. However, four deprecated tools could be pruned, and the count is on the heavy side compared to typical MCP servers. It feels overengineered, yet each tool addresses a distinct facet of the platform.
The toolset covers the full lifecycle: discovery, evaluation, purchase, delivery, feedback, business management, policy, storefront, and distribution. Gaps are minor—for example, no direct way to list all services with full details without service_list, but that exists. The deprecated tools indicate ongoing migration to a consolidated search surface, suggesting good coverage. A few small gaps remain (e.g., no explicit 'update listing' for buyers, but that may not be needed).