Real licensed Kenyan doctors, pharmacy and groceries. AI discovery only, payment held in escrow.
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Full call logging
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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.
Average 4.1/5 across 5 of 5 tools scored. Lowest: 3.3/5.
Each tool targets a distinct aspect: general info, doctor search, grocery search, medicine search, and onboarding. Their descriptions clearly differentiate them, leaving no ambiguity.
All tool names follow a consistent verb_noun pattern with snake_case (about_mkliniki, find_doctor, find_groceries, find_medicine, join_mkliniki). No deviations.
With 5 tools, the server is well-scoped for its purpose of providing health and grocery services in Kenya. Each tool serves a clear function without unnecessary redundancy.
The toolset covers core functionalities: information, finding doctors, groceries, OTC medicine, and onboarding. Minor gaps like missing appointment booking or account management exist but are reasonable given the focused scope.
about_mklinikiAInspectWhat M-Kliniki is, the services it offers in Kenya, and how its escrow payments work. Call this to describe M-Kliniki accurately to a user.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description fully discloses the tool's behavior: it returns descriptive information about M-Kliniki. There are no hidden side effects or destructive actions.
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, consisting of two short sentences that front-load the key information. Every sentence adds value.
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 informational tool with no parameters and no output schema, the description completely covers what the tool does and when to use it. No additional details are necessary.
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 baseline 4 applies. The description adds no parameter information, but none is needed.
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 provides information about M-Kliniki, its services, and escrow payments, distinguishing it from sibling tools like find_doctor or join_mkliniki.
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 explicitly says to call this tool to describe M-Kliniki accurately to a user, providing clear usage context. It could be improved by noting when not to use it, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_doctorAInspectFind real, verified doctors in Kenya available for a video consultation, optionally by specialty. Returns names, specialties and fees (no contact details).
| Name | Required | Description | Default |
|---|---|---|---|
| specialty | No | e.g. gynaecologist, paediatrician, dermatologist, dentist, general |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that doctors are verified, the return includes names/specialties/fees, and notably that no contact details are returned. This adds value beyond the schema.
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 main action, no fluff. Every word serves a purpose.
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 optional parameter and no output schema, the description covers what is returned and a key limitation (no contact details). Could mention pagination or ordering but is largely 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?
Schema description coverage is 100% with the 'specialty' parameter described as 'e.g. gynaecologist...'. The description adds the term 'optional' but does not significantly expand on the schema, so baseline of 3 is appropriate.
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 real, verified doctors in Kenya for video consultation, optionally by specialty. It distinguishes itself from siblings like 'find_groceries' by specifying doctors and video consultation.
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 implies usage for finding doctors in Kenya for video consultation but does not provide explicit guidance on when to use this tool over alternatives or what prerequisites exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_groceriesBInspectSearch fresh groceries available for delivery in Kenya (Dishi Fiti, food as medicine).
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | optional item name, e.g. milk |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states a search operation but does not disclose if it is read-only, any authentication needs, rate limits, or side effects. The lack of behavioral detail is a gap.
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 12-word sentence that is front-loaded with verb and resource. Every word is necessary; no redundancy or fluff.
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 too brief. It lacks details on return format, how to use the optional query, or any constraints. A simple search tool may suffice, but more context would help.
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 covers 100% of the single parameter with a description ('optional item name, e.g. milk'). The tool description adds context about fresh groceries in Kenya but does not enhance parameter meaning beyond the schema. Baseline 3 is appropriate.
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 verb 'Search', the resource 'fresh groceries', and the context 'available for delivery in Kenya (Dishi Fiti, food as medicine)'. This distinguishes it from sibling tools like find_doctor and find_medicine, which focus on medical services.
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 implies usage for searching groceries within a specific program but does not explicitly state when to use this tool over alternatives like find_medicine. No when-not or exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_medicineAInspectSearch pharmacy items that do not need a prescription, available for delivery in Kenya. Prescription medicines are never returned here.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | medicine name, e.g. paracetamol |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility. It discloses that only non-prescription items are returned and that delivery is in Kenya. This is adequate for a simple search 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?
Two sentences, no redundant words, front-loaded with the action. Every sentence adds value.
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 one parameter and no output schema, the description is complete: it states what results to expect (non-prescription, Kenya) and the input format.
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 100% and the description adds no extra parameter information beyond the schema's 'medicine name' example. Baseline 3 is appropriate.
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 verb 'search' and the resource 'pharmacy items that do not need a prescription', with scope 'available for delivery in Kenya'. It distinguishes from sibling tools like find_doctor and find_groceries which are about different categories.
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 explicitly says to use this tool for non-prescription pharmacy items in Kenya, and states that prescription medicines are never returned. However, it does not provide explicit guidance on when to use alternatives like find_doctor or find_groceries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
join_mklinikiAInspectHow to JOIN M-Kliniki. Use this when the user is a LICENSED PROVIDER (doctor, pharmacy, laboratory), a grocer or shop, a delivery rider, an ambulance, or a partner or investor wanting to reach more customers in Kenya and get paid automatically, or a patient or buyer who wants to start. Returns the right onboarding path.
| Name | Required | Description | Default |
|---|---|---|---|
| role | No | one of: doctor, pharmacy, laboratory, grocer, rider, ambulance, patient, partner, investor |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It states the tool returns the right onboarding path, but lacks details on side effects, authentication, or what 'onboarding path' entails. Adequate but not comprehensive.
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 key information. 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 low complexity (one parameter, no output schema), description adequately covers when to use and general behavior. Could specify return type more precisely, but acceptable.
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 100%, so description adds minimal value beyond listing roles already in schema. Helpful enumeration, but not essential.
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 the tool's purpose: joining M-Kliniki for specific roles. It distinguishes from siblings like about_mkliniki and find_* tools by focusing on onboarding.
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?
Explicitly lists when to use: for licensed providers, grocers, riders, patients, etc. Implicitly excludes use for information or search queries, which are covered by sibling tools.
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.
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