Call For Me
Server Details
Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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.
Tool Definition Quality
Average 4.6/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: place_call initiates a call and returns an ID, while get_call_status polls for the outcome. There is no overlap or ambiguity.
Both tools use consistent snake_case with a verb_noun pattern (place_call, get_call_status), making the convention predictable and easy to follow.
With only two tools, the set is minimal but well-scoped for the core workflow of placing a call and checking its status. It is slightly undercounted but reasonable for this narrow domain.
The tools cover the essential call lifecycle (place and poll status). A minor gap is the lack of a cancel or list calls feature, but the core task is fully supported.
Available Tools
2 toolsget_call_statusAInspect
Poll the status of a call previously placed with place_call. Returns a CallOutcome with one of these statuses (in roughly likely order): queued/placing/ringing/connected — call still in progress, poll again in a few seconds completed — call finished cleanly, structured result available partial — call finished but some questions unanswered voicemail — recipient was voicemail; identified message left no_answer — recipient never picked up busy — recipient line was busy invalid_number — number is not in service rejected_ai — recipient declined to talk to A.I. (do not retry) needs_user_input — recipient needs info only the user can provide online_only — recipient said the task can only be done online timed_out — call exceeded max duration carrier_failure — telephony provider error (safe to retry later) api_error — internal failure (safe to retry)
Always carries a free-form exit_reason string suitable for showing the user.
| Name | Required | Description | Default |
|---|---|---|---|
| call_id | Yes | The call_id returned by place_call. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully explains the returned CallOutcome and each status. Could explicitly state it's read-only, but the polling nature implies 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?
Two-sentence structure with clear purpose first, then a well-organized list of statuses. 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?
Comprehensive for a polling tool: explains input, output, status meanings, and retry logic. No missing context.
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?
Only one parameter (call_id), schema already covers its purpose. Description reinforces by linking to place_call and the polling 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 states it polls call status after place_call, and lists all possible statuses. This distinguishes it from sibling tool place_call.
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 says to poll after placing a call, provides polling intervals for in-progress statuses, and gives retry advice for final statuses (e.g., 'do not retry' for rejected_ai).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
place_callAInspect
Place an outbound phone call to a US business or person. The A.I. assistant on the call will identify itself as A.I., follow your instructions, and return a structured outcome via get_call_status.
USE THIS TOOL WHEN: the user wants to make a phone call, contact a business by phone, ask about hours/pricing/availability, book a reservation, gather info that's not online, follow up on a service request, or do any task that requires talking to a human on the phone.
LIMITATIONS:
US phone numbers only (E.164 starting with +1). International is not yet supported.
English language only.
Cannot call emergency services (911, 988, etc.) — these will be rejected.
The A.I. will NOT commit to bookings/payments without user confirmation unless safety.must_confirm_with_user is explicitly set to false.
Default 5-minute call duration cap.
Returns immediately with a call_id. Poll get_call_status(call_id) for the result.
| Name | Required | Description | Default |
|---|---|---|---|
| user | Yes | ||
| safety | No | ||
| target | Yes | ||
| instructions | Yes | The conversation goals/script the AI should follow. Agent owns this. We wrap it with mandatory safety layer (disclosure, hangup, voicemail, graceful-exit rubric). Be specific — what to ask, what tone, what to do if recipient declines. | |
| output_schema | No | JSON Schema for the structured outcome you want extracted from the transcript. | |
| idempotency_key | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses AI identity, structured outcome via get_call_status, call duration cap, and restrictions. Could add more on error handling or rate limits, but covers key behaviors.
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?
Description is well-structured with sections and bullet points, no wasted sentences. Each line adds value, from purpose to limitations to output pattern.
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?
Covers purpose, limitations, output pattern (call_id + poll), and mentions sibling tool. Given 6 parameters and no output schema, slightly more detail on safety settings or output_schema parameter could improve, but overall 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?
Schema description coverage is 33%, so description must compensate. It mentions 'instructions' and 'output_schema' and explains the return flow, but does not detail 'user', 'target', or 'safety' parameters beyond schema. Adequate but not rich.
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 'Place' and the resource 'an outbound phone call to a US business or person', and distinguishes from sibling 'get_call_status' which is for polling results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists usage scenarios with 'USE THIS TOOL WHEN:' and includes limitations (US only, English, no emergency calls, commitment rules). Clearly separates when to use this vs. polling with sibling.
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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For users:
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Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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