RecallChecker — Vehicle Safety Recalls
Server Details
Check U.S. NHTSA vehicle safety recall campaigns by make, model, and year. Live official data.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- ollo12-prog/recallchecker
- GitHub Stars
- 0
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.6/5 across 1 of 1 tools scored.
With only one tool, there is no possibility for confusion or overlap between tools. Disambiguation is not a concern in this case.
There is only one tool, so there is no inconsistency in naming patterns. The name 'check_vehicle_recalls' follows a clear verb_noun structure.
A single tool is slightly thin for a server dedicated to vehicle safety recalls, as users may expect additional functionality like VIN-specific lookups or recall detail retrieval. However, the tool is well-scoped to a specific common use case.
The tool only provides recall checks by make, model, and year, missing the crucial VIN-specific lookup that is often required for individual vehicle status. This is a significant gap for users wanting to check their own vehicle's recall status.
Available Tools
1 toolcheck_vehicle_recallsCheck vehicle safety recalls (NHTSA)ARead-onlyInspect
Check U.S. NHTSA safety recall campaigns for a vehicle by make, model, and model year. Returns official NHTSA recall campaigns (component, hazard, remedy, campaign number, official notice link) plus the date the data was fetched. Results are model-year campaign matches, NOT VIN-specific repair status — an empty result means no open recalls were found in NHTSA as of the returned date, which is not a guarantee the vehicle is safe.
| Name | Required | Description | Default |
|---|---|---|---|
| make | Yes | Vehicle make, e.g. Honda, Ford, Toyota | |
| year | Yes | Four-digit model year, e.g. 2021 | |
| model | Yes | Vehicle model, e.g. Civic, F-150, Camry |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint. The description adds critical behavioral context: it returns official recall info with a date, and clarifies that an empty result does not imply vehicle safety. No contradictions with 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?
The description is two sentences with no extraneous words. The purpose is front-loaded in the first sentence, and the second sentence covers critical limitations.
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's simplicity (three required params, no output schema), the description is nearly complete. It describes return fields (component, hazard, remedy, campaign number, link, date) and limitations. Lacking only a structured output example.
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 100% with clear descriptions for each parameter (make, model, year). The description does not add additional parameter-level meaning beyond what the schema provides.
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 checks U.S. NHTSA safety recall campaigns for a vehicle by make, model, and model year. It specifies the resource (NHTSA) and scope, making it distinct from any potential alternatives.
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?
The description provides explicit guidance: results are model-year campaign matches, not VIN-specific repair status, and an empty result does not guarantee safety. This clarifies when to use this tool and its limitations.
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.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
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.
Discussions
No comments yet. Be the first to start the discussion!