Corvi Careers
Server Details
Search remote and onsite jobs through the public Corvi Careers MCP server.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- jobswithgpt/mcp
- 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 2.7/5 across 4 of 4 tools scored.
Each tool has a clear, distinct purpose: listing categories, autocompleting locations, looking up companies, and searching jobs. No overlap.
All tool names follow a consistent verb_noun pattern with snake_case (list_categories, location_autocomplete, lookup_companies, search_jobs).
4 tools is well-scoped for a job search server, covering essential filter helpers without being excessive or insufficient.
The set covers key search-related operations, but lacks a dedicated tool for retrieving full job details or additional filters (e.g., job type), though the search tool likely subsumes those.
Available Tools
4 toolslist_categoriesAInspect
List valid category slugs
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only says 'list', implying a read operation, but lacks details on authorization, rate limits, or possible side effects.
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 with four words, highly concise and front-loaded. Every word is necessary and contributes directly to understanding.
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 no output schema and no annotations, the description is minimal. It explains the basic function but omits what a 'category slug' is or what the output looks like, which could confuse an agent without prior context.
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?
The tool has no parameters, so the schema coverage is 100%. Per the rule '0 params = baseline 4', the description adds no extra meaning, which is acceptable given no parameters to document.
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?
Description 'List valid category slugs' clearly states the action (list) and the resource (valid category slugs). It distinguishes from sibling tools (location_autocomplete, lookup_companies, search_jobs) which serve different purposes.
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 this tool versus alternatives. The description does not mention prerequisites, context, or exclusions, leaving the agent with no basis for comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
location_autocompleteCInspect
Find matching locations for job search filters
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| min_population | No | ||
| include_country | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears full burden. It only states a generic action ('Find matching locations') without disclosing any behavioral traits such as rate limits, data freshness, or query handling.
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, making it concise but overly minimal. It lacks structure and does not front-load key information.
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 four parameters and no output schema or annotations, the description is insufficient. It omits crucial details like return format, pagination, and edge cases.
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 does not explain any of the four parameters (limit, query, min_population, include_country), leaving the agent without actionable detail.
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 finds matching locations for job search filters, distinguishing it from siblings like list_categories, lookup_companies, and search_jobs. However, it doesn't explicitly mention the autocomplete behavior.
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 is provided on when to use this tool versus alternatives, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lookup_companiesCInspect
Find matching company names
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states 'Find matching company names' with no details on matching algorithm, result limits, pagination, or idempotency, leaving significant gaps.
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 under-specified. It lacks structure and important details, making it minimally acceptable but not efficiently informative.
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 no annotations, no output schema, and 0% schema coverage, the description fails to cover essential context like return format, behavior with missing parameters, or error handling. It is insufficient for an agent to use correctly.
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 0% and the description adds no meaning to the two parameters (query, limit). The agent gets no help understanding what 'query' expects or how 'limit' affects results.
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 finds matching company names (verb+resource). It implicitly suggests a search/lookup function, which is distinct from sibling tools like list_categories and location_autocomplete, though it does not explicitly differentiate.
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 this tool versus siblings. The description lacks context for appropriate use cases or exclusions, leaving the agent to infer from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_jobsCInspect
Search for jobs by keywords, locations, titles, companies, and categories
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| query | No | ||
| remote | No | ||
| titles | No | ||
| recency | No | ||
| distance | No | ||
| job_type | No | ||
| keywords | No | ||
| companies | No | ||
| job_level | No | ||
| job_types | No | ||
| locations | No | ||
| geonameids | No | ||
| job_levels | No | ||
| geoname_ids | No | ||
| recency_days | No | ||
| category_slug | No | ||
| category_slugs | No | ||
| negative_keywords | No | ||
| category_hierarchy | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It only says 'search', implying read-only, but no details on pagination, result limits, searching semantics (exact vs fuzzy), or data freshness. No behavioral traits beyond the basic operation.
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, front-loading the core purpose. It is not verbose, but given the tool's complexity with 21 parameters, it could benefit from structured formatting (e.g., bullet points) without becoming long.
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?
Despite the tool having 21 parameters, no output schema, and no annotations, the description provides minimal context. Missing: pagination behavior, default limits, output structure, or how to effectively narrow results. The description is insufficient for an agent to reliably invoke the tool.
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%, yet the description only mentions keywords, locations, titles, companies, and categories. Many parameters (page, limit, remote, job_type, recency, distance, negative_keywords, etc.) are omitted. No explanation of parameter interactions, formats, or preferred combinations.
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 'Search for jobs' indicating a search operation on jobs resource, and lists several filter dimensions. However, it does not differentiate from sibling tools like list_categories or lookup_companies, which could be used for related tasks.
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 this tool versus alternatives. With 21 optional parameters, the agent receives no hints on which parameters to prefer or how to combine them. There is no mention of prerequisites or 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.
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