leximo-ai-call-assistant-mcp-server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@leximo-ai-call-assistant-mcp-serverSchedule a call to +1234567890 to confirm appointment"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Leximo AI Call Assistant — MCP Server
An MCP (Model Context Protocol) server that lets you schedule AI phone calls and manage Leximo assignments directly from Claude Desktop or Claude Code — no app switching needed.
Quick Install
Claude Code (one command)
claude mcp add leximo -e LEXIMO_API_TOKEN=your-token -- npx -y leximo-ai-call-assistant-mcp-serverReplace your-token with your API token from concierge.leximo.ai/profile.
Claude Code (plugin marketplace)
/plugin marketplace add leximo-ai/leximo-ai-call-assistant-mcp-serverThen install the plugin:
/plugin install leximo-ai-call-assistantRelated MCP server: hermes-mcp
Manual Setup
1. Get your API token
Go to concierge.leximo.ai and sign in
Open your profile page
Copy your JWT access token
2. Configure Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"leximo": {
"command": "npx",
"args": ["-y", "leximo-ai-call-assistant-mcp-server"],
"env": {
"LEXIMO_API_TOKEN": "your-token"
}
}
}
}3. Configure Claude Code (manual)
Add to your Claude Code MCP settings:
{
"mcpServers": {
"leximo": {
"command": "npx",
"args": ["-y", "leximo-ai-call-assistant-mcp-server"],
"env": {
"LEXIMO_API_TOKEN": "your-token"
}
}
}
}Features
Assignments — Create, list, view, and delete AI phone call assignments
AI Agents — Browse available calling agents and pick the right one
Task Proposals — Get AI-generated improvements for your call instructions
Credits — Check your credit balance and usage history
Subscriptions — View your plan, browse available plans, and subscribe
Notifications — View call completion events and system notifications
Available Tools
Tool | Description |
| Get your user profile and account details |
| Check credit balance, usage history, and subscription summary |
| View active subscription details |
| List available subscription plans with pricing |
| Get a checkout URL to subscribe to a plan |
| List available AI calling agents |
| Get details of a specific agent |
| List all your assignments (paginated) |
| View a specific assignment with results and transcript |
| Create a new phone call assignment |
| Delete an assignment |
| Get AI suggestions to improve your task description |
| Get call completion events and notifications |
Example Prompts
Once configured, ask Claude things like:
"Show me my Leximo assignments"
"Create a call to +1234567890 to book a restaurant for 2 at 7pm Friday"
"How many credits do I have left?"
"What subscription plans are available?"
"Show me the transcript from my last call"
"What agents are available and which one is best for restaurant bookings?"
Development
npm install
npm run build # Compile TypeScript
npm start # Run compiled server
npm run dev # Run with tsx (hot reload)Test with MCP Inspector
LEXIMO_API_TOKEN=your-token npx @modelcontextprotocol/inspector node dist/index.jsEnvironment Variables
Variable | Required | Description |
| Yes | JWT token from concierge.leximo.ai/profile |
Copy .env.example to .env for local development.
License
Available Tools
13 toolscreate_assignmentA
Create a new phone call assignment. Do NOT call this tool immediately. Follow this workflow:
Gather info: Ask the user for any missing details — phone number, desired call time, timezone, and language. Do NOT guess or fabricate values.
Select agent: Call list_agents to show available agents. Recommend one based on the task or let the user choose.
Improve task: Call get_assignment_proposals with the user's task description, then present the enhanced version for the user to approve or edit.
Confirm: Summarize all parameters (agent, name, datetime, timezone, phone number, language, task) and get user confirmation before calling this tool. Only call create_assignment after completing all steps above.
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | Yes | ID of the AI agent to use. Call list_agents first to see available agents. | |
| name | Yes | Name for this assignment (e.g. the business or person being called) | |
| datetime | Yes | When to make the call, in ISO 8601 format (e.g. 2025-06-15T14:30:00) | |
| timezone | Yes | Timezone for the datetime (e.g. America/New_York, Europe/London) | |
| phoneNumber | Yes | Phone number to call in international format (e.g. +1234567890) | |
| languageCode | Yes | Language code for the call (e.g. en, es, fr, de) | |
| task | Yes | Description of what the AI agent should do during the call (e.g. 'Book a table for 2 at 7pm on Friday') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It discloses the creation action but does not discuss side effects (e.g., whether scheduling is immediate, if it sends notifications, or requires special permissions). The workflow hints at safety (user confirmation) but lacks explicit behavioral traits beyond 'create'.
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 front-loaded with the core purpose and immediate prohibition. The workflow is detailed but each sentence is necessary for safe operation. Slightly longer than ideal but earns its length through clarity and procedural 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?
The description fully covers the tool's preconditions, required parameters, and user confirmation step. Despite no output schema, it provides enough context for an agent to use the tool correctly within the defined workflow. No gaps identified.
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 each parameter has a clear schema description. The description adds workflow context (e.g., 'do not guess values') but does not provide semantic detail beyond the schema. Baseline score 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 explicitly states 'Create a new phone call assignment' with a specific verb and resource. It clearly distinguishes from sibling tools like list_agents, get_assignment_proposals, and delete_assignment by embedding the tool in a multi-step workflow.
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 a complete step-by-step workflow: gather info, select agent via list_agents, improve task via get_assignment_proposals, confirm with user, and only then call this tool. It explicitly warns 'Do NOT call this tool immediately' and identifies prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_checkout_sessionA
Create a Stripe checkout session to subscribe to a plan. Returns a URL the user should open in their browser to complete payment.
| Name | Required | Description | Default |
|---|---|---|---|
| priceId | Yes | Stripe price ID from the get_plans tool |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it creates a session and returns a URL, which implies a mutation. However, it doesn't disclose potential side effects, rate limits, or session expiration, making it minimally adequate.
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 short sentences, each earning its place. No 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?
With one required parameter and a simple return value (URL), the description covers the essential information: what it does, what input is needed, and what output to expect. It lacks details like error cases or timeouts, but overall 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?
Schema coverage is 100% with a description for priceId. The description adds value by noting the priceId comes from get_plans, providing context beyond 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 clearly states the tool's action (create a Stripe checkout session) and its purpose (to subscribe to a plan). It also explains the return value (URL for payment). It distinguishes from siblings like get_plans and get_subscription.
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 implicitly guides usage by specifying that the priceId comes from the get_plans tool, indicating a prerequisite. It doesn't explicitly list when not to use, but given the context, it's clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_assignmentB
Delete an assignment by its ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Assignment identifier |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Only states 'delete' with no disclosure of consequences (e.g., permanence, cascading effects, permissions) beyond the annotation-less tool's implicit 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?
Single sentence with no waste, but could add minimal context (e.g., confirmation) without harming conciseness.
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?
Adequate for a simple delete with one param, but lacks usage guidelines and behavioral transparency for full 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?
Schema coverage is 100% for the single parameter 'id'; description adds no extra meaning beyond the schema's 'Assignment identifier'.
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?
Clear verb 'delete' and resource 'assignment', distinguished from sibling tools like create_assignment and get_assignment.
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 or when not to use this tool compared to alternatives; no prerequisites or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_agentB
Get details of a specific AI calling agent by ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Agent identifier |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description indicates a read operation but lacks details on authentication, rate limits, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no superfluous words; 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?
Adequate for a simple retrieval tool with one parameter, but missing details about return value fields and potential errors.
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 the single parameter fully; description adds minimal extra meaning beyond 'by ID'.
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 retrieves details of a specific agent identified by ID, distinguishing it from list_agents which returns multiple agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like list_agents, nor any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_assignmentA
Get a single assignment by its ID, including call results, transcript, and recording URL
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Assignment identifier |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the tool returns a single assignment with specific data, implying a read-only operation. No side effects, auth needs, or rate limits are mentioned, but for a simple get, the disclosure is sufficient.
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, front-loaded with action and key inclusions. No wasted words. Efficient for an agent to parse.
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 (one param, no output schema), the description adequately covers purpose and return content. Could mention error handling or structure, but the core use case is well described.
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 only parameter 'id' is documented in the schema as 'Assignment identifier'. The description adds minimal extra meaning ('by its ID'). Since schema coverage is 100%, baseline is 3.
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 a single assignment by ID, specifying the included data (call results, transcript, recording URL). It distinguishes from siblings like list_assignments (multiple) and create/delete (write 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 when an assignment ID is known, but lacks explicit guidance on when not to use this tool versus alternatives like get_assignment_proposals. No exclusions or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_assignment_proposalsA
Get AI-generated enhancement proposals for a task description. IMPORTANT: Always call this BEFORE create_assignment to improve the task instructions. Pass the user's task description and present the enhanced suggestions to the user for approval before proceeding with assignment creation.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Natural language description of the assignment task |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It describes what the tool returns but does not explicitly state it is read-only or non-destructive. Could improve by noting no side effects.
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 important usage instruction in caps. Efficient and no fluff, though could be slightly more concise by integrating the instruction into the first sentence.
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 (1 param, no output schema), description covers purpose and usage workflow. Missing return format but adequate for the tool's 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?
Schema coverage is 100%, and description adds 'Pass the user's task description' which essentially repeats the schema's description. No additional semantic 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 gets AI-generated enhancement proposals for a task description, using a specific verb and resource. It also distinguishes from sibling tool create_assignment by indicating it should be called before it.
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?
Explicit guidelines: 'Always call this BEFORE create_assignment' and 'present the enhanced suggestions to the user for approval'. Provides clear workflow context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_creditsA
Get credit balance, monthly allowance, usage history, and subscription summary for the authenticated user
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'for the authenticated user,' implying authentication is required, which adds some behavioral context. However, no annotations exist, and the description does not disclose other behavioral traits like idempotency, rate limits, or side effects.
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 sentence that conveys all necessary information without redundancy. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (no parameters, no output schema), the description provides adequate context. It explains what data is returned, though it omits the structure or format of the response.
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 the schema coverage is 100%. The description does not need to add parameter information, and it correctly omits any.
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 what the tool does: retrieving credit balance, monthly allowance, usage history, and subscription summary. It uses a specific verb and resource, and distinguishes from siblings like get_subscription and get_plans.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like get_subscription or get_plans. It does not mention prerequisites or contexts where this should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_plansA
List available subscription plans with pricing information
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 accurately describes a straightforward read-only list operation. For a simple tool with no parameters, this is sufficient.
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 that conveys the tool's purpose without any unnecessary words 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 simple listing tool with no parameters and no output schema, the description is largely complete. It explains the tool's output type and could optionally add more detail about the return format, but the current level 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?
There are no parameters, so the baseline is 4. The description does not need to add parameter information, and schema coverage is trivially 100%.
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 lists subscription plans with pricing, using the specific verb 'List' and resource 'subscription plans'. It is unambiguous and distinguishes from sibling tools like get_subscription.
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 needing to view plans/pricing, but does not explicitly state when not to use or suggest alternatives. This is adequate for a simple listing tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_profileA
Get the authenticated user's profile information including email, credits, and account details
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It mentions 'authenticated user', implying authentication is required, but does not detail side effects, rate limits, or error conditions. For a simple read, this is 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 sentence with action, resource, and examples. It is front-loaded and contains no fluff, earning high marks for conciseness.
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, the description lists some fields but is not exhaustive. It provides a general idea of return data but lacks detail on structure or mandatory fields. Acceptable for simple tool but not fully 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?
There are no parameters, so schema coverage is 100%. The description adds no param info, which is acceptable as baseline for zero 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 'Get' and the specific resource 'authenticated user's profile information', and lists example fields (email, credits, account details). It distinguishes itself from sibling tools which handle assignments, agents, etc.
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 retrieving profile data of the authenticated user, but does not provide explicit guidance on when to use or not use it, nor contrasts it with alternatives. While siblings are different, no usage context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_subscriptionA
Get the active Stripe subscription details for the authenticated user
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden; it only states 'Get' (a read operation) but does not disclose authentication requirements, potential errors (e.g., no subscription), or response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, efficiently conveying 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?
Given no annotations or output schema, the description is adequate for a zero-parameter read tool but lacks details about the return value or error states, leaving some uncertainty.
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, so schema coverage is 100%; the description adds no redundant information and is sufficient.
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 the specific verb 'Get', identifies the resource 'active Stripe subscription details', and scopes it to 'the authenticated user', clearly distinguishing it from siblings like 'get_plans' or 'create_checkout_session'.
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 retrieving the current user's subscription but provides no explicit guidance on when to use or avoid this tool, nor does it suggest alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_agentsA
List all available AI calling agents. IMPORTANT: Always call this BEFORE creating an assignment. Present the returned agents to the user so they can choose which one should make the call, or recommend one based on the user's task. The agent's ID is required for create_assignment.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 implicitly indicates a read-only operation (listing) but does not explicitly state that no modifications occur. The context of listing is clear, but additional transparency about safety could improve it.
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?
Three sentences with no wasted words. The critical usage guidance (call before create_assignment) is emphasized and front-loaded, making it easy to parse.
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 absence of an output schema, the description does not detail the structure of returned agents. However, it sufficiently conveys the purpose and how to use the output (e.g., agent ID for create_assignment). A slight addition of common fields would make it more complete.
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 schema coverage is 100%. The description appropriately focuses on usage without needing parameter details, meeting the baseline for zero-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 clearly states the tool lists all available AI calling agents, using a specific verb and resource. It distinguishes itself from siblings like get_agent (which retrieves a single agent) and other assignment tools.
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 instructs to call this before create_assignment, advises to present agents to the user or recommend one, and explains the importance of the agent ID for the next step.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_assignmentsB
List assignments (call tasks) for the authenticated user with pagination. Returns data, total, page, limit, and totalPages.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number (default: 1) | |
| limit | No | Items per page (default: 20) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions pagination and return fields but omits whether the operation is read-only, any rate limits, required permissions beyond authentication, or side effects. For a list operation, this is minimally 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 sentence that contains all essential information (verb, resource, scope, pagination) without fluff. Every word 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?
For a simple paginated list tool with 2 parameters and no output schema, the description is adequate but incomplete: it does not specify ordering, filters (e.g., status), or whether all assignments or only active ones are returned. The stated return structure (data, total, page, limit, totalPages) is helpful.
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% (both page and limit have descriptions with defaults). The description adds no additional meaning beyond what the schema provides, so a baseline score 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 'List assignments (call tasks) for the authenticated user with pagination,' providing the specific verb (list), resource (assignments/call tasks), and scope (for authenticated user). It distinguishes itself from siblings like get_assignment (singular) and create/delete actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide when-to-use or when-not-to-use guidance, nor does it mention alternatives among sibling tools (e.g., get_assignment for a single item). The only context is 'for the authenticated user,' but no exclusion criteria or comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_notificationsA
Get paginated list of notifications for the current user. Includes call completion events and system notifications.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of notifications to return (default: 20, max: 100) | |
| offset | No | Number of notifications to skip (default: 0) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions 'paginated list' and the types of notifications, but does not disclose behavioral traits like authentication requirements, ordering, filtering capabilities, or rate limits. The description is moderately helpful but lacks depth.
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 wasted words. It front-loads the purpose and includes relevant details about content type.
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 (2 parameters, no output schema, no nested objects), the description covers the essentials. Lacks return structure details, but the expected output is implied. For a list tool, this is 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% with clear parameter descriptions (limit with default and max, offset with default). The description adds no additional meaning beyond the schema, so 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 'Get', the resource 'paginated list of notifications', and the scope 'for the current user'. It also specifies the types of notifications included (call completion events and system notifications), which distinguishes it from sibling tools that deal with assignments, agents, etc.
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?
While the description does not explicitly state when to use this tool vs alternatives, the context of sibling tools shows no other tool listing notifications, so the purpose is clear. A minor improvement would be an explicit 'Use this to...' statement, but it's adequate.
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.
13 tool updates
v1.0.1- First observed
create_assignment - First observed
create_checkout_session - First observed
delete_assignment - First observed
get_agent - First observed
get_assignment - First observed
get_assignment_proposals - First observed
get_credits - First observed
get_plans - First observed
get_profile - First observed
get_subscription - First observed
list_agents - First observed
list_assignments - First observed
list_notifications
TDQS
All 13 tools have clearly distinct purposes. There is no overlap; each tool targets a unique resource or action, such as creating vs. listing assignments, retrieving agents, or managing subscriptions.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_assignment, list_agents, get_credits). No mixing of conventions or ambiguous verbs.
With 13 tools, the set is well-scoped for the server's purpose (AI calling assignments and subscription management). Each tool has a clear role, and there are no extraneous tools.
The tool surface covers core workflows: assignment CRUD (except update), agent management, subscription management, and notifications. Missing an update_assignment tool is a minor gap, but the design intentionally uses creation via proposals.
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