Evidence-backed migration resolution for obsolete industrial components. Returns conditional migration candidates, OEM evidence, unresolved context, and machine-readable next actions.
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Average 2.1/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of confusion with other tools. The tool's purpose is fully scoped by its own description, making disambiguation trivially perfect.
With only one tool, naming patterns cannot be evaluated or compared. The tool name itself uses an underscore between 'resolve' and 'migration' but there is no pattern to assess consistency.
A single tool is inadequate for almost any server purpose. Even for a highly specialized migration tool, you would expect at least a few operations such as resolve, list, get_details, or rollback. One tool suggests either extreme minimalism or an incomplete implementation.
A migration resolver that only provides a single 'resolve' operation is severely incomplete. There is no ability to view/examine exceptions before resolving, no reporting, no rollback capability, and no way to list or filter exceptions. The tool surface has critical gaps that would likely cause agent failures in most workflows.
resolve_migration_exceptionCInspectResolve obsolete industrial component migration exceptions using evidence-backed structured data.
| Name | Required | Description | Default |
|---|---|---|---|
| part_number | Yes | ||
| manufacturer | No | ||
| known_context | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must convey all behavioral traits. It only says 'resolve using evidence-backed structured data', leaving the agent uncertain about side effects, idempotency, error handling, or what the tool actually does to the system.
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 sentence, which is concise but at the expense of critical information. It does not front-load important details; it is under-specified for a tool with three parameters and no other documentation.
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 three parameters (including a nested object), no output schema, and no annotations, the description is grossly incomplete. It provides no information about return values, error states, or the semantics of 'resolve', leaving the agent unable to use the tool correctly without external knowledge.
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 description coverage is 0%, and the description adds no explanation of parameters. The parameter names (part_number, manufacturer, known_context) are somewhat self-explanatory, but the nested object known_context and its structure are completely undocumented. The agent has no guidance on how to fill in these fields.
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 action ('Resolve') and the resource ('obsolete industrial component migration exceptions'). It is specific and distinct, though it could elaborate on what 'resolve' entails in terms of outcome.
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?
No guidance on when to use or avoid this tool. No sibling tools are provided, but even without alternatives, there is no context about prerequisites, input conditions, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
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Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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