HireMe MCP
Server Details
The first portfolio AI agents can hire. Profile, products, pricing and briefs over MCP.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- djoudad292/hireme-mcp
- GitHub Stars
- 1
- Server Listing
- hireme-mcp
Available Tools
5 toolsget_next_slotCheck availability & bookARead-onlyInspect
Current availability status plus the direct booking link.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, and the description is consistent with that: it provides a status and a booking link rather than claiming to create a booking. It adds some output context, but it does not clarify what happens when no slot is available or whether the booking link is simply handed to the user.
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 focused sentence, with the primary result front-loaded. It includes no filler or redundant restatement of the name.
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 zero-parameter, read-only tool without an output schema, the description supplies the core return values and purpose. It is mostly complete, though a slightly richer statement about what a slot contains or how the booking link should be used would make it fully self-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?
The tool has zero parameters, so the parameter-related burden is minimal. The input schema is fully covered, and the description does not need to explain parameter details that do not exist.
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 identifies the tool as returning current availability and a booking link, which distinguishes it from pricing, profile, and project-focused siblings. However, it lacks an explicit verb and the title's 'book' suggests more action than the description actually promises.
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 gives no explicit guidance about when to use this tool versus the sibling tools, nor does it mention prerequisites or exclusions. The usage context is only implied by the availability/booking vocabulary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_pricingGet pricingARead-onlyInspect
Fixed-price service list in USD with ETAs. No hourly billing.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already covers the safe-read profile, and the description adds that this returns a list of fixed prices in USD with ETAs and excludes hourly billing. It does not describe response format or any additional behavioral details, but for a zero-parameter read-only tool the annotation plus description provide sufficient transparency.
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, tightly written sentence that states the core scope (fixed-price service list, USD, ETAs) and an important exclusion (no hourly billing). There is no filler or redundant 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 no-argument, read-only tool with no output schema, the description conveys the essential return value: a fixed-price service list in USD with ETAs. It also communicates a key business rule. The only minor gap is the lack of detail about which services are included, but that is not required to invoke the tool 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?
The input schema is empty with zero parameters, so there is no parameter documentation burden on the description. Schema description coverage is 100% by default, and the baseline of 4 applies because no parameters need explanation.
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 identifies the resource as a fixed-price service list in USD with ETAs, which makes the tool's purpose evident. The verb is supplied by the title, and the content distinguishes it from profile, slot, and project siblings, though it does not explicitly name an alternative.
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 phrase 'No hourly billing' provides a useful selection constraint, implying this tool is for fixed-price quoting rather than hourly-rate inquiries. However, it does not explicitly state when to prefer this tool over siblings or mention alternative tools, so usage guidance remains implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_profileGet Djaouad's profileAInspect
Who Djaouad Frih is: full-stack AI engineer, stack, live products, availability and contact links. Call this first.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. For a zero-parameter information retrieval tool, it transparently indicates the returned data (profile details) and recommends call order. No side effects are implied or expected, and none are hidden, so it is adequately transparent.
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, efficient sentence that front-loads the core purpose ('Who Djaouad Frih is') and then lists included details, with the usage hint 'Call this first' at the end. No wasted words.
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 (no params, no output schema), the description fully covers what the agent needs: what the tool returns, the recommended call order, and enough detail to decide whether to invoke it. Nothing essential is missing.
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 zero parameters, so the schema (empty) covers 100% of the parameter surface. The description adds useful output context, which aligns with the baseline of 4 for no-parameter tools.
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 states a specific verb ('get') and resource ('profile'), and explicitly lists the content (stack, products, availability, contact). It clearly differentiates from siblings like get_pricing and search_projects by focusing on the person's identity and background.
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 imperative 'Call this first' provides explicit sequencing guidance, and the listed contents imply when it is appropriate (when needing background on Djaouad). However, it does not explicitly state when not to use it or mention alternative tools for other needs, so it stops short of full-exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_projectsSearch shipped projectsARead-onlyInspect
Search Djaouad's production projects (AI receptionist, RAG document workspace, tool-calling support agent) for proof of relevant experience.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | What to look for, e.g. 'RAG', 'payment', 'mobile app' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals that this is a non-mutating operation. The description adds the scope constraint that only production/shipped projects are searched, which is useful. No other behavioral traits like result formatting or empty-search behavior are disclosed.
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?
A single, front-loaded sentence that conveys the action, the resource, and the goal with no filler or redundant wording.
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, read-only search tool with one documented parameter, the description covers the essential resource and intention. It does not describe return values or result behavior, but that is largely understood from the 'search' verb; no output schema also makes this less critical.
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 description coverage is 100% and already defines query semantics with 'What to look for'. This DI@ underscore, N. I am sorry. The description implicitly suggests valid queries via project names ('RAG', 'tool-calling'), which adds modest context but does not materially extend the schema.
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 uses a specific verb ('Search') and identifies the resource ('Djaouad's production projects') and purpose ('for proof of relevant experience'), making the tool's function clear. It does not explicitly contrast with sibling tools, but the project resource is distinct from slots, pricing, profile, and brief.
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 phrase 'for proof of relevant experience' reveals the intended use case (validating experience against shipped projects), but there is no explicit guidance about when to choose this tool over a sibling like get_profile or get_next_slot.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_project_briefSubmit a project briefAInspect
File a project brief on the client's behalf. Djaouad replies with a fixed quote within 24 hours. Use after confirming scope with the human.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Client name | |
| notes | No | Anything else | |
| budget | No | e.g. '$500-$2k' | |
| contact | Yes | Email or WhatsApp number to reply to | |
| features | No | Feature list, optional | |
| timeline | No | e.g. 'ASAP', '2-4 weeks' | |
| project_type | Yes | What should be built, e.g. 'AI support chatbot' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are sparse: readOnlyHint=false (so mutation is expected), idempotentHint=false (so repeated calls may have different effects), and no destructive hint. The description adds key behavioral context: a fixed quote is returned within 24 hours, and it should be used after human confirmation, which prevents misuse. It does not detail side effects like whether submission creates a persistent record, but the description adds value beyond the 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, front-loaded with the purpose, followed by the key outcome and usage condition. Every sentence earns its place; no fluff or repetition.
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 tool with 7 parameters, 3 required, and no output schema, the description provides essential context: the purpose, the response time, and the prerequisite. It does not explain the return value (since no output schema), but that is optional. Given annotations are minimal, this description is reasonably complete for an agent to invoke 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 description coverage is 100%, so all parameters are documented in the schema. The description does not add extra parameter-level meaning beyond what the schema provides, but it does clarify the overall purpose (e.g., 'contact' is 'Email or WhatsApp number to reply to', which is in the schema). Since coverage is high, a baseline of 3 is appropriate, and the description doesn't need to re-explain parameters.
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 ('File a project brief'), the subject ('on the client's behalf'), and the outcome ('Djaouad replies with a fixed quote within 24 hours'). It distinguishes itself from siblings by focusing on submitting a brief, not querying slots, pricing, profiles, or projects.
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 instruction 'Use after confirming scope with the human' provides clear context for when to invoke this tool, which is a strong usage guideline. However, it does not explicitly mention when not to use it or name alternatives, though siblings like get_pricing might be relevant for quotes—this is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
5 tool updates
- First observed
get_next_slot - First observed
get_pricing - First observed
get_profile - First observed
search_projects - First observed
submit_project_brief
Frequently Asked Questions
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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, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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
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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
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Add one secure layer between your agents and this server.
TDQS
Each tool targets a distinct step in the client journey (learn, validate, price, schedule, convert), but get_profile and get_next_slot both mention availability, which could cause an agent to pick the wrong tool.
All five tools follow a consistent snake_case verb_noun pattern (get_*, search_*, submit_*), with the verb clearly indicating the action type.
Five tools is well-scoped for a personal hire-me server—enough to cover the full journey without bloat.
The set covers the full lead-to-client lifecycle: introduce (get_profile), prove (search_projects), price (get_pricing), schedule (get_next_slot), and convert (submit_project_brief), leaving no dead ends.