Read-only senior-care exit routes, duplicate-referral deadlines, and templates; no PII or sending.
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.
Average 4.2/5 across 7 of 7 tools scored.
Most tools have clearly distinct purposes: get_info, get_location, get_services, lookup_deadline, lookup_exit_route, choose_workflow, and template retrieval are all separate concerns. However, get_info and get_services both touch on pricing/options, which could cause slight confusion.
All tool names follow a consistent verb_noun pattern in snake_case (get_*, lookup_*, choose_*). The verbs are semantically appropriate, and the style is uniform throughout, making the set predictable.
With 7 tools, the set is well-scoped for a niche informational server focused on referral exit routes and deadlines. Each tool covers a distinct aspect, and the count does not feel excessive or sparse.
The toolset covers key information retrieval (business info, services, location), lookup of deadlines and exit routes, and workflow selection. A minor gap is the lack of a tool to list all supported networks, which would improve discoverability, but agents can work around this.
choose_private_workflowChoose the smallest GeezerKeeper workflowAChoose the free, $19 consumer, or $59 professional option using only recipient count and intended use. No personal information is accepted.
| Name | Required | Description | Default |
|---|---|---|---|
| recipientCount | Yes | Number of identifiable organizations to track | |
| professionalUse | No | True for a practice, firm, or senior living location sharing handouts or tracking referral chronology and deadlines |
| Name | Required | Description |
|---|---|---|
| reason | Yes | |
| alternatives | Yes | |
| dataHandling | Yes | |
| nextActionUrl | Yes | |
| recommendation | Yes | |
| userFacingSummary | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's a safe read operation. The description adds the behavioral constraint 'No personal information is accepted,' which is valuable beyond the annotations and signals input restrictions.
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?
One efficient sentence conveying the core function and a key constraint. No redundancy; title and description are both concise.
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 selection tool with two params and an output schema, the description is sufficient. It doesn't spell out return values, but the output schema covers that. Slight gap: doesn't explain what the chosen workflow entails, but not necessary for 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 100%, with clear descriptions for recipientCount and professionalUse. The description's phrase 'using only recipient count and intended use' loosely maps to the schema but adds no new details beyond what's already in the parameter descriptions.
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 'Choose the free, $19 consumer, or $59 professional option' which identifies the tool's function as selecting a plan/workflow. The title 'Choose the smallest GeezerKeeper workflow' adds specificity. This distinguishes it from sibling tools which are all get/lookup operations.
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 selecting among pricing tiers based on recipientCount and professionalUse, but doesn't explicitly state when to use it versus the sibling lookup tools. No exclusions or alternative recommendations are provided, so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_infoGet canonical GeezerKeeper business informationAReturn canonical public business identity, contact, pricing range, and privacy-boundary information (PUBLICMCP v0.3). Accepts no inputs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| logo | Yes | |
| name | Yes | |
| contact | Yes | |
| tagline | Yes | |
| website | Yes | |
| category | Yes | |
| description | Yes | |
| price_range | Yes | |
| business_type | Yes | |
| data_boundary | Yes | |
| opening_hours | Yes | |
| social_profiles | Yes | |
| publicmcp_version | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds context by noting the information is public and canonical, and explicitly mentions 'privacy-boundary information,' indicating what is not included (private data). This goes beyond the structured annotations, enhancing 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 concise sentence, front-loaded with the action and key details. It includes only necessary information (what is returned, public nature, version tag, no inputs) without any fluff 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?
Given the tool's low complexity (no parameters), rich annotations (read-only, idempotent), and an output schema, the description is fully sufficient. It covers what information is returned and notes the privacy boundary, leaving no critical gaps for an agent to invoke this 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 tool has zero parameters, and the schema fully captures this (100% coverage). Per the rubric, 0 params earns a baseline of 4. The description repeats 'Accepts no inputs,' which confirms but does not add meaning beyond the schema. This is acceptable and consistent.
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 canonical public business identity, contact, pricing range, and privacy-boundary information. The verb 'Return' and specific resource categories make the purpose unambiguous. It distinguishes from sibling tools like get_location and get_services by focusing on canonical business-level information.
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 when one needs the listed business information, but it does not explicitly mention alternatives or when not to use it. Sibling tool names provide context, but the description lacks direct guidance on tool selection, so usage is only inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_locationGet GeezerKeeper delivery coverageAReturn online delivery and U.S. service coverage without exposing a private street address or accepting a location input.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| geo | Yes | |
| offices | Yes | |
| geo_radius | Yes | |
| scope_note | Yes | |
| headquarters | Yes | |
| service_areas | Yes | |
| remote_capable | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to restate safety. It adds value by disclosing the privacy behavior ('without exposing a private street address') and the lack of location input, which are not captured in the annotations. This is useful behavioral context beyond the structured metadata.
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 conveys purpose, scope, and a key behavioral constraint without any redundant wording. Every phrase earns its place, making it highly concise and well-structured.
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 parameters), rich annotations, and presence of an output schema, the description provides sufficient context. It explains what the tool returns and the privacy design, which fully addresses the tool's purpose and limitations for an agent.
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 and the schema is empty, so schema description coverage is 100% by default. Per the baseline for 0 parameters, the description does not need to compensate for missing parameter details, and it correctly confirms that no location input is accepted.
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's action ('Return online delivery and U.S. service coverage') and specifies the resource and scope. It also distinguishes itself by noting it does not accept a location input or expose a private address, setting it apart from sibling tools that might take location parameters.
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 when to use the tool: when coverage information is needed without requiring a location input or risking private address disclosure. It does not explicitly name alternatives or exclusions, but the context is clear for a zero-parameter tool that returns coverage data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_servicesGet GeezerKeeper services and current pricesAReturn the current free, $19 consumer, and $59 professional self-serve options. The optional category is enumerated and cannot carry personal information.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter: all, free, consumer, or professional | all |
| Name | Required | Description |
|---|---|---|
| services | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description adds that the category parameter is enumerated and cannot carry personal information. This is a useful privacy constraint beyond the schema, but the description does not disclose potential rate limits or data freshness details.
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, front-loaded with the primary function, and contains no unnecessary words 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?
For a simple read-only service with an output schema and full annotations, the description covers the essential behavior and parameter constraint. No significant gaps are evident.
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 already fully documents the category parameter with enum and default. The description adds meaning by linking categories to specific prices ($19 consumer, $59 professional), helping agents understand the significance of each enum value.
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 the current service tiers and prices, specifically listing free, $19 consumer, and $59 professional options. This clearly distinguishes it from sibling tools like get_info or get_location.
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. The description simply states what it returns without contrasting it with other tools or specifying use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_unfilled_request_templateGet an unfilled stop-contact request templateAReturn an unfilled template for a referral network or an identifiable provider. The server accepts no personal fields and never sends the request. Replace bracketed placeholders locally.
| Name | Required | Description | Default |
|---|---|---|---|
| sourceId | Yes | Used only to return the current source-specific destination and instructions | |
| recipientType | Yes | Return a template for the referral network or for one identified provider |
| Name | Required | Description |
|---|---|---|
| sourceId | Yes | |
| template | Yes | |
| disclaimer | Yes | |
| destination | Yes | |
| dataBoundary | Yes | |
| recipientType | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable context beyond the annotations: 'The server accepts no personal fields and never sends the request' clarifies the privacy and non-transmission behavior, and 'Replace bracketed placeholders locally' tells the user what to do with the result. This supplements the readOnly and idempotent hints.
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, tightly packed with essential information. It is front-loaded with the primary purpose and uses no filler 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?
The tool is simple, has an output schema, and full parameter coverage. The description covers the core behavior, local handling, and safety guarantees, making it complete for the tool's complexity.
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 both parameters well-documented via enums and descriptions. The tool description does not significantly add meaning beyond the schema, so it stays at the baseline score.
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 starts with 'Return an unfilled template for a referral network or an identifiable provider,' which clearly states the verb (return), resource (template), and target recipients. This distinguishes it from sibling tools like get_info or get_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 makes it clear that this tool is for obtaining a template that is filled locally, not for sending requests. It implies the intended use case but does not explicitly name alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lookup_duplicate_referral_deadlineLook up a senior-living duplicate-referral deadlineAReturn source-maintained public duplicate-referral deadline and reporting-route facts for Caring.com or A Place for Mom, plus the current professional tracking fit. Input is only an enumerated network; never provide lead or prospect information.
| Name | Required | Description | Default |
|---|---|---|---|
| network | No | Filter: all, caring, or apfm | all |
| Name | Required | Description |
|---|---|---|
| policies | Yes | |
| disclaimer | Yes | |
| reviewedAt | Yes | |
| dataBoundary | Yes | |
| professionalFit | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds meaningful context by specifying that data is 'source-maintained public' and includes a warning about not providing lead/prospect information, going beyond the structured annotations. It does not contradict any 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, no wasted words. The first sentence packs the object and scope; the second provides a clear usage constraint. Structure is front-loaded with the main action.
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 one-parameter tool with output schema and annotations, the description covers the core purpose, input constraints, and data source. It could be slightly more explicit about when to use vs. siblings, but overall is adequate for 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 100% with an enum and description for the single 'network' parameter. The description reinforces the boundary ('only an enumerated network') but adds little beyond the schema's existing documentation. Baseline 3 applies.
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 the tool returns 'source-maintained public duplicate-referral deadline and reporting-route facts' for Caring.com or A Place for Mom, clearly specifying the verb and resource. It also mentions 'current professional tracking fit', and the title echoes the same. This distinguishes it from siblings like lookup_exit_route.
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 on what the tool accepts ('Input is only an enumerated network') and an explicit exclusion ('never provide lead or prospect information'). It does not explicitly name alternatives, but the boundary is clear enough for an agent to know 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.
lookup_exit_routeLook up a senior-care referral exit routeAReturn a maintained stop-contact and privacy route for one supported senior-care referral network. Input is only a network identifier; never provide personal information.
| Name | Required | Description | Default |
|---|---|---|---|
| sourceId | Yes | Referral network: apfm, caring, seniorly, or seniorhousingnet |
| Name | Required | Description |
|---|---|---|
| route | Yes | |
| guideUrl | Yes | |
| nextStep | Yes | |
| disclaimer | Yes | |
| reviewedAt | Yes | |
| dataBoundary | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description need not repeat safety traits. It adds valuable context beyond annotations by noting that the route is 'maintained' (curated, not dynamic) and that personal information should never be provided, which clarifies data handling expectations. No contradiction 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, front-loaded with the main purpose, and contains no filler. Every clause earns its place by clarifying the scope ('one supported... network') and the privacy constraint ('never provide personal 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, strong annotations, and an output schema, the description covers the essential aspects: what it returns, its maintained/privacy nature, and the input constraint. It lacks explicit comparison with sibling tools, but that is a minor gap given the low complexity and richness of other structured fields.
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 fully documents the single parameter sourceId with an enum and explicit description, so schema coverage is 100%. The description merely restates that input is a network identifier, adding no new semantic detail beyond what the schema already provides. 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 verb 'Return' and the specific resource: a 'maintained stop-contact and privacy route' for 'one supported senior-care referral network.' This distinguishes it from sibling tools like get_info, get_location, and get_services by focusing on a unique route object, and the scope ('one... network') is explicit.
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 the tool is used when you need an exit route for a referral network, and it gives an explicit input constraint ('Input is only a network identifier; never provide personal information'). However, it does not mention when to prefer this over sibling tools or provide any exclusions, so usage guidance is only implied rather than fully explicit.
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.
No comments yet. Be the first to start the discussion!