Remoote Remote Jobs MCP
Server Details
Search remote jobs, compare salaries, create alerts, and request user-confirmed apply links.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- asmisha/remoote-mcp
- GitHub Stars
- 0
- Server Listing
- remoote-mcp
Tool Definition Quality
Average 3.2/5 across 6 of 6 tools scored.
Each tool targets a distinct action: fetching a single job, searching, salary stats, top jobs, creating an alert, and applying. Even search_jobs and get_top_jobs are differentiated by popularity vs. search criteria.
All tools follow a consistent snake_case verb_noun pattern (create_*, get_*, search_*). This makes the API predictable and easy to navigate.
Six tools cover the core job board functions without bloat or redundancy. The count feels well-scoped for a focused remote jobs API.
Core workflows (search, view, stats, alerts, apply) are covered. Missing update/delete for alerts and apply intents are minor gaps, but the main public-facing job retrieval is complete.
Available Tools
6 toolscreate_alertCInspect
Create a daily or weekly Remoote job alert for the authenticated user. Requires the alerts:write scope.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| limit | No | ||
| criteria | Yes | ||
| frequency | No | daily |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions the required 'alerts:write' scope, but does not disclose idempotency, response behavior, or side effects. Minimal disclosure.
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?
Single sentence, concise and front-loaded. However, could add more value without losing conciseness, e.g., mentioning key parameters.
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?
Tool has multiple parameters including a nested criteria object with many fields, no output schema. Description insufficient to understand input structure or tool behavior.
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%, yet description adds no parameter details beyond implying frequency. Four parameters exist (name, limit, criteria, frequency) with a complex criteria object, none explained.
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 clearly states it creates a job alert, specifies 'daily or weekly' and 'for authenticated user'. Distinguishes from siblings which are about applying, getting jobs, salary stats, top jobs, or searching.
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 vs alternatives. Only mentions a required scope, but no comparison with siblings or conditions for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_apply_intentBInspect
Create a user-confirmed Remoote apply redirect for an authenticated agent token. Requires the apply:intent scope and never returns raw employer apply URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose all behavioral traits. It mentions the scope requirement and the fact that raw URLs are not returned, but it omits other important behaviors such as side effects (e.g., creating records), rate limits, authentication requirements beyond the scope, or error conditions. The description is insufficient for a mutation tool.
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 that front-loads the core purpose and includes key constraints. There is no redundant or unnecessary text, making it appropriately sized and efficient.
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 low complexity (1 parameter, no output schema, no nested objects), the description provides a basic purpose and constraints. However, it lacks details about the 'user-confirmed' aspect, how the agent token is used, and the nature of the redirect. The information is adequate but not fully complete for an agent to use confidently.
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 input schema has one parameter, 'job_id', with type integer and exclusiveMinimum 0. The schema description coverage is 0%, meaning the description does not explain the parameter. The description adds no information about 'job_id' beyond what the schema already provides, failing to compensate for low coverage.
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 creates a 'user-confirmed Remoote apply redirect' for an authenticated agent token, specifying a specific action and resource. However, it does not differentiate from siblings; the siblings are distinct in function (e.g., search, get), so the purpose is clear but could be more specific about what 'Remoote apply redirect' entails.
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 mentions the required scope ('apply:intent') and a behavioral constraint ('never returns raw employer apply URLs'), which provides usage context. However, it does not explicitly state when to use this tool versus alternatives, nor does it exclude any scenarios. The guidelines are present but minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_jobAInspect
Fetch public details for one active Remoote job, including salary, location, skills, excerpts, and a Remoote job URL.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It indicates it is a read-only operation ('Fetch public details'), but does not mention rate limits, authentication requirements, error scenarios (e.g., job not found), or any side effects. Some behavioral context is present, but gaps remain.
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, well-structured sentence that is front-loaded with the core action and immediately lists key returned fields. No extraneous 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?
For a simple tool with one parameter and no output schema, the description covers the purpose and return fields adequately. Minor gaps include missing usage guidance and behavioral nuances like what happens if the job ID is invalid.
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 schema has one parameter (job_id) with no description coverage. The description only implies job_id identifies a job but adds no additional format details or constraints beyond the schema. This is adequate but does not simplify use for the agent.
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 ('Fetch'), the resource ('one active Remoote job'), and lists specific fields included (salary, location, skills, etc.). It distinguishes from sibling tools like search_jobs which return multiple jobs.
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 does not explicitly state when to use this tool versus alternatives (e.g., search_jobs for multiple jobs). It implies use when you have a specific job ID, but no direct guidance on when not to use or what prerequisites are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_salary_statsCInspect
Return salary stats for active Remoote jobs matching supported filters when enough normalized compensation data exists.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | ||
| region | No | ||
| skills | No | ||
| country | No | ||
| seniority | No | ||
| company_id | No | ||
| location_tag | No | ||
| exclude_skills | No | ||
| employment_type | No | ||
| salary_required | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the burden. It mentions the condition 'when enough normalized compensation data exists,' which is a useful behavioral note. However, it lacks details on authentication, rate limits, or response format.
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 concise at one sentence and front-loaded with the action. It could be expanded to cover key parameters or use cases without becoming verbose.
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?
No output schema, so the description should hint at return values (e.g., aggregated stats). It does not. With 10 parameters and no behavioral annotations, the description is insufficient for an agent to use the tool effectively.
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 provides no param-level details. With 10 parameters, the description should clarify their roles beyond the schema (e.g., what 'query' means). The current description is inadequate.
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 it returns salary stats for active Remoote jobs with filters, distinguishing it from sibling tools like search_jobs and get_job which focus on individual job listings. However, it could specify what statistics are returned (e.g., median, range).
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 explicit guidance on when to use this tool versus alternatives. The description references 'supported filters' but does not elaborate on which filters are supported or provide context for selecting this tool over search_jobs or get_top_jobs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_top_jobsBInspect
Return a capped public list of currently popular Remoote remote jobs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions the list is 'public' and 'capped,' but does not disclose authentication needs, rate limits, or whether it is read-only. Minimal behavioral context beyond the basic function.
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?
Single sentence with no redundant words. Every word contributes to understanding the tool's function.
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?
For a simple tool with one parameter and no output schema, the description is somewhat complete. However, it lacks details about the returned job data structure, which is needed for an agent to know what to expect. Does not leverage output schema (missing) to compensate.
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%, yet the description does not explain the `limit` parameter (its purpose, default, range). The word 'capped' hints at limiting but gives no concrete parameter semantics. This is a significant gap.
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 returns a 'capped public list of currently popular remote jobs.' This distinguishes it from sibling tools like search_jobs (search) and get_job (single job). The verb 'Return' and resource 'list of popular jobs' are specific.
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 like search_jobs or get_job. The description implies it's for discovering popular jobs, but does not explicitly state when it is preferred or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_jobsAInspect
Search active Remoote remote jobs. Use role_title to match job titles and query for broad keyword search. Returns capped public results with canonical Remoote URLs and no raw employer apply URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | Broad full-text keyword search across the whole job posting (title, description, skills). | |
| region | No | ||
| skills | No | ||
| country | No | ||
| seniority | No | ||
| role_title | No | Role/job title phrase matched against job titles only, e.g. 'backend engineer'. Use for role searches; combine with query for extra keywords. | |
| location_tag | No | ||
| exclude_skills | No | ||
| employment_type | No | ||
| salary_required | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on the transparency burden and directly discloses key behaviors: it returns capped public results, provides canonical Remoote URLs, and excludes raw employer apply URLs. It also narrows scope to 'active' remote jobs, which is useful. It does not cover other behaviors like authentication or rate limits, but the disclosed limitations are significant.
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, front-loaded with the primary action, each sentence adds meaningful value. No filler or redundancy.
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?
The tool has 11 parameters and no output schema, making it complex and in need of richer description. The description only mentions result capping and URL types, but fails to clarify expected return format, filter combinations, default behavior, or the meaning of salary_required. It is inadequate for correct agent selection and invocation.
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 only 18% (2 of 11 parameters described). The description compensates partially by explaining role_title and query, but the other 9 parameters (limit, region, skills, country, seniority, etc.) receive no guidance in either the schema or description. This is insufficient for such a high-parameter tool.
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 active Remoote remote jobs', naming a specific verb and resource. It distinguishes itself from siblings like get_job (specific job) and get_top_jobs by focusing on searching active remote jobs.
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 clear context for when to use the tool (searching jobs) and gives practical guidance on using role_title vs query. It does not explicitly mention when not to use it or name alternatives, but the distinction from siblings is implicit through the word 'search'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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.
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