MCP server for Jeremy Twogood, Toronto video producer & editor. Projects, reel, resume, booking.
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Tool access control
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 3.8/5 across 10 of 10 tools scored. Lowest: 3.1/5.
Each tool targets a distinct purpose: booking calls, retrieving different types of project details, listing projects, getting profile/resume/reel, and sending messages. There is no overlap that would confuse an agent.
The naming convention is mostly verb_noun in snake_case (e.g., book_call, get_profile, list_projects). Minor deviations like get_reel (informal noun) and send_message (verb_object) are still clear and don't disrupt pattern recognition.
10 tools is well-scoped for a portfolio server. Each tool serves a necessary function without redundancy, covering profile, projects, booking, and messaging. The count feels natural and complete.
The tool set covers the main portfolio interactions: viewing profile, resume, reels, projects (with two categories), booking a call, and sending a message. A minor gap is lack of search or filtering for projects, but the core lifecycle is present.
book_callAInspectGet a pre-filled Calendly booking link for a call with Jeremy. Requires agent_name and human_name. Rate limited to 3 action requests per IP per day.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_name | Yes | Your agent name or identifier, e.g. "Claude" | |
| human_name | Yes | The name of the human you represent |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the rate limit, which is behavioral, but lacks clarity on whether the tool is read-only or creates a booking. Without annotations, the agent might assume it is a mutation.
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 with no extraneous information, efficiently conveying purpose, requirements, and a constraint.
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 low-complexity tool with no output schema, the description covers the main points: what it does, required parameters, and a rate limit. It does not specify the return format beyond 'pre-filled link', but that is likely 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 coverage is 100%, and the description merely restates the parameter names without adding additional meaning beyond what the schema already provides.
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 'get' and the resource 'pre-filled Calendly booking link for a call with Jeremy', distinguishing it from sibling tools that list or retrieve other resources.
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?
It mentions required parameters and a rate limit, but does not provide explicit guidance on when to use this tool over alternatives like send_message, 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.
get_ai_buildAInspectGet full details for a single AI or software project.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Build ID — get valid IDs from list_ai_builds |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only says 'Get full details' without disclosing side effects, authentication requirements, rate limits, or what constitutes 'full details'. This is a significant gap for a single-purpose 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 with no wasted words. It is front-loaded with the key information (action and resource).
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 description is adequate for a simple retrieval tool with one parameter, but lacks details about the output structure or what 'full details' encompasses. Given no output schema, the description could have been more informative.
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% (the 'id' parameter has a clear description). The tool description adds no further meaning beyond the schema, so it meets the baseline but does not enhance understanding of the output or parameter behavior.
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 ('Get') and resource ('full details for a single AI or software project'). It distinguishes from the sibling 'list_ai_builds' (list vs. get) and implies a specific resource type not covered by 'get_project'.
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 implicit guidance via the 'id' parameter's schema description ('get valid IDs from list_ai_builds'), but does not explicitly state when to use this tool over alternatives 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.
get_availabilityAInspectGet Jeremy's booking URL and availability information.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It states it retrieves a booking URL and availability but gives no details on side effects, authentication requirements, or what availability information means (e.g., time slots, dates).
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, no redundant information. Front-loaded with the key action and resource.
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 description is sufficient for a simple tool with no parameters, but lacks details on what availability information includes and how it relates to book_call. Additional context on return values or usage would improve completeness.
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?
No parameters exist, so schema coverage is 100% trivially. The description adds context about the output (booking URL and availability), which provides value beyond the empty 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?
Description clearly states the action (get) and resource (Jeremy's booking URL and availability information). It distinguishes from siblings like book_call by focusing on retrieval rather than booking.
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 like book_call or other get tools. The description does not mention scenarios where this tool is appropriate or when it is not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_profileAInspectGet Jeremy Twogood's profile — bio, skills, clients, location, and social links.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It indicates a read operation but does not disclose any behavioral details (e.g., idempotency, rate limits, or authentication). For a simple get tool, this is minimally adequate but not thorough.
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, front-loaded sentence with no wasted words. Every word contributes meaning.
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 that there are no parameters and no output schema, the description sufficiently enumerates the key data returned (bio, skills, clients, location, social links), making it complete for a profile retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and schema coverage is 100%. The description adds value by listing the fields included in the profile, which compensates for the lack of parameter information.
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 'Get' and the resource 'Jeremy Twogood's profile', listing specific contents (bio, skills, clients, location, social links). It is distinct from sibling tools like get_resume or get_reel, making the purpose unambiguous.
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 no guidance on when to use this tool versus alternatives, nor any exclusions or context about prerequisites. It simply states what it does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_projectAInspectGet full details for a single project, including video content description.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Project ID — get valid IDs from list_projects |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states 'Get full details' indicating a read operation, but does not disclose any potential side effects, authorization requirements, or rate limits. For a simple getter, this is adequate but not rich.
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 with no filler words. It efficiently conveys the tool's 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?
There is no output schema, so the description must hint at return values. It mentions 'full details' and 'video content description', but lacks specificity about other fields. Given the tool's simplicity, it is acceptable but could be more comprehensive.
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 100% coverage with a description for the 'id' parameter that instructs to get valid IDs from 'list_projects'. The tool description adds information about the return content (video content description), which complements the schema. Since schema coverage is high, the description adds meaningful return context.
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 specifies the verb 'Get' and the resource 'project', and adds context about returning 'full details, including video content description'. It distinguishes from sibling tools like 'list_projects' which lists projects, and 'get_ai_build' which targets a different resource.
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 when-to-use or when-not-to-use guidance is given. However, the parameter description in the schema implicitly suggests usage after listing projects, and the tool name and description imply it's for fetching a single project. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_reelAInspectGet Jeremy's showreel description and link.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It does not mention that the operation is read-only, whether authentication is needed, or any side effects. The description merely repeats the purpose without adding behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundancy. It is front-loaded and efficiently conveys the necessary 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?
While the description specifies the output contains 'description and link,' it lacks details about the return format (e.g., JSON structure, field names). Given no output schema, this is a noticeable gap, but the low complexity makes it minimally adequate.
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?
There are zero parameters, and the schema coverage is 100%. The description adds value by indicating the output contains 'description and link,' which is not evident from the schema alone. Baseline 4 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 retrieves 'Jeremy's showreel description and link,' which is a specific verb and resource. It distinguishes itself from sibling getters like get_profile or get_resume by targeting the showreel uniquely.
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 over alternatives. The description only states what it does, without context such as prerequisites or comparison to sibling tools like get_profile.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_resumeAInspectGet Jeremy's full structured resume as JSON.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the output format (JSON) and that it returns the full resume, but lacks details like idempotency, side effects, or authentication needs. For a simple retrieval, this is adequate but minimal.
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 sentence, front-loaded with the action and resource. 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 zero parameters, no output schema, and a simple operation, the description is complete enough. It fully specifies what the tool returns. Could mention its read-only nature, but not 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?
There are no parameters (0), so the baseline is 4. The description does not need to add parameter meaning, and it correctly implies no arguments are 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 action (Get) and the resource (Jeremy's full structured resume as JSON). It distinguishes from sibling tools like get_profile, get_project, etc., which are for different resources.
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 you need Jeremy's resume) but provides no explicit guidance on when to use vs alternatives or when not to use. No exclusions or context are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_ai_buildsBInspectList all of Jeremy's AI and software projects.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It only states the basic action without disclosing ordering, pagination, or what constitutes AI/software projects. Minimal behavioral context.
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 concise sentence that conveys the core purpose. Could incorporate more detail but remains 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?
With no output schema or annotations, description provides adequate but not complete context. It does not explain return format or what properties each project includes. Leaves room for ambiguity.
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?
Zero parameters, so baseline is 4. Description adds meaning by specifying the scope (Jeremy's AI and software projects) beyond the empty schema. Acceptable.
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 lists Jeremy's AI and software projects, specifying the resource and scope. However, it does not explicitly differentiate from sibling list_projects, which might overlap.
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 siblings like list_projects or get_ai_build. Implied usage for AI/software projects but lacks conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_projectsAInspectList all of Jeremy's work projects with metadata.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool lists projects with metadata, which implies a read-only operation, but does not detail any behavioral traits like authentication requirements or performance characteristics. Adequate for a simple list 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 of 7 words, containing only essential information without any redundancy. It is maximally concise and front-loaded.
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 has no parameters, no output schema, and is a straightforward list operation, the description fully covers what is needed. It is complete for its simplicity.
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 input schema coverage is 100%. Per the rubric, 0 parameters defaults to a baseline of 4. The description adds no parameter information, which is acceptable since no parameters 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 states the action ('List') and resource ('projects') and adds specificity with 'Jeremy's work projects with metadata', distinguishing it from sibling tools like get_project and list_ai_builds.
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 (when you need a list of work projects) but does not provide explicit guidelines on when not to use or alternatives. Since the tool is simple with no parameters, the lack of explicit guidance is acceptable but not exemplary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_messageAInspectSend a message to Jeremy by email. Requires agent_name (your identifier) and human_name (the person you represent). Rate limited to 3 action requests per IP per day.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | The message to send to Jeremy | |
| agent_name | Yes | Your agent name or identifier, e.g. "Claude" | |
| human_name | Yes | The name of the human you represent |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses a key behavioral trait: rate limit of 3 action requests per IP per day. It does not detail side effects, idempotency, or error behavior, but this is sufficient for a simple email send.
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 with no extraneous information. The main action is front-loaded, followed by requirements and constraints. Every sentence earns its place.
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 simplicity of the tool (3 params, no nested objects, no output schema), the description covers the essential information: purpose, required parameters, and a behavioral constraint. It could mention that the message is sent to a specific recipient, but it is adequate.
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%, baseline 3. The description adds value by explaining the purpose of agent_name (identifier) and human_name (represented person), which clarifies usage beyond the schema 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 'Send a message to Jeremy by email,' which is a specific verb-resource pair. It distinguishes from sibling tools that are primarily retrieval-oriented (get/list).
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 specifies required parameters (agent_name, human_name) and provides context for when to use the tool. However, it does not explicitly exclude scenarios or mention alternatives, though siblings suggest no other messaging tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
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