Superforms
Server Details
Human-input bridge for AI agents with voice-first answer links, MCP tools, and HTTP APIs.
- 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 3/5 across 8 of 8 tools scored.
Multiple tools have overlapping purposes: create_ask is an alias for create_form, and create_feedback_form is similar. Additionally, join_creation_session and update_creation_session are closely related, causing potential confusion.
All tool names follow a consistent snake_case verb_noun pattern (e.g., create_form, get_responses, join_creation_session), making them predictable and easy to understand.
The tool count of 8 is well-scoped for a voice-first form creation and response retrieval service, covering essential operations without being excessive.
The tool set covers form creation, response retrieval, and session management, but lacks update/delete operations for forms and a tool to list all forms, leaving notable gaps.
Available Tools
8 toolscreate_askCreate Superforms AskCInspect
Create a voice-first Superforms answer link for human input. Backward-compatible alias for create_form.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | ||
| title | No | ||
| prompt | No | Plain-English ask or request. Use only when explicit questions are not already known. | |
| context | No | Hidden context for the form. | |
| questions | No | Explicit questions to ask the respondent. Use this whenever questions already exist; preserve them exactly. | |
| persistent | No | ||
| followUpMode | No | ||
| responseMode | No | ||
| responseLimit | No | Use "one" for a form intended for one named person/client. Use "multiple" for forms, surveys, feedback, customers, users, and public/embedded links. | |
| questionContext | No | ||
| creationSessionUrl | No | ||
| max_total_questions | No | Total question safety cap. Use 20 for open-ended feedback conversations. | |
| max_followups_per_question | No | Maximum AI follow-up questions per specified question. Use 1 for optional specified-question follow-ups. |
Tool Definition Quality
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 it creates an answer link, but does not disclose behavioral traits such as destructive nature, required permissions, rate limits, or side effects beyond creation. Minimal 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 brief and to the point, consisting of two sentences with no unnecessary words. It front-loads the key action, earning a high score 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 the complexity (13 parameters, no output schema, nested objects), the description is too minimal. It does not explain return values, prerequisites, or how this tool relates to siblings beyond being an alias. Incomplete for a tool of this 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?
The input schema has 46% parameter description coverage, but the tool description adds no additional parameter semantics beyond what is in the schema. For a tool with many parameters, the description should compensate but does not.
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 creates a 'voice-first Superforms answer link for human input' and notes it is an alias for create_form. Purpose is specific, but it does not differentiate from sibling create_feedback_form, leaving some ambiguity.
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 only mentions it is a backward-compatible alias for create_form, but provides no explicit guidance on when to use this tool versus alternatives like create_feedback_form or create_form. No when-to-use or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_feedback_formCreate Feedback FormCInspect
Create a voice-first feedback, cancellation, feature request, survey, or research form with optional smart follow-ups.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | ||
| title | No | ||
| prompt | No | Plain-English ask or request. Use only when explicit questions are not already known. | |
| context | No | Hidden context for the form. | |
| questions | No | Explicit questions to ask the respondent. Use this whenever questions already exist; preserve them exactly. | |
| persistent | No | ||
| followUpMode | No | ||
| responseMode | No | ||
| responseLimit | No | Use "one" for a form intended for one named person/client. Use "multiple" for forms, surveys, feedback, customers, users, and public/embedded links. | |
| questionContext | No | ||
| creationSessionUrl | No | ||
| max_total_questions | No | Total question safety cap. Use 20 for open-ended feedback conversations. | |
| max_followups_per_question | No | Maximum AI follow-up questions per specified question. Use 1 for optional specified-question follow-ups. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'voice-first' and 'optional smart follow-ups' but does not disclose whether creation is idempotent, destructive, or requires specific permissions. No details on side effects or limitations.
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 efficiently conveys the tool's purpose and key features. It is front-loaded with the main action and type, though additional structure could improve readability.
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 complexity (13 parameters, nested objects, no output schema), the description is minimal. It does not explain return values, behavior, prerequisites, or provide examples, leaving significant gaps for the 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?
Schema coverage is only 46%, and several parameters (goal, title, context, persistent, followUpMode, responseMode, questionContext, creationSessionUrl) lack descriptions. The description only implies the followUpMode via 'smart follow-ups' but does not clarify other parameters. It does not compensate for the low coverage.
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 creates a voice-first feedback form for various use cases like feedback, cancellation, feature request, survey, or research. The verb 'Create' and resource 'feedback form' are specific, but it doesn't explicitly differentiate from sibling tools like create_ask or create_form, though the specialization is implied.
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 lists the types of forms it can create, but provides no guidance on when to use this tool versus alternatives like create_ask or create_form. No exclusions or conditional usage advice is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_formCreate Superforms FormCInspect
Create a voice-first form link that collects human answers and pipes responses back to the agent.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | ||
| title | No | ||
| prompt | No | Plain-English ask or request. Use only when explicit questions are not already known. | |
| context | No | Hidden context for the form. | |
| questions | No | Explicit questions to ask the respondent. Use this whenever questions already exist; preserve them exactly. | |
| persistent | No | ||
| followUpMode | No | ||
| responseMode | No | ||
| responseLimit | No | Use "one" for a form intended for one named person/client. Use "multiple" for forms, surveys, feedback, customers, users, and public/embedded links. | |
| questionContext | No | ||
| creationSessionUrl | No | ||
| max_total_questions | No | Total question safety cap. Use 20 for open-ended feedback conversations. | |
| max_followups_per_question | No | Maximum AI follow-up questions per specified question. Use 1 for optional specified-question follow-ups. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only mentions creation and piping of responses, but does not address potential side effects, authorization needs, or rate limits. The description is too brief to be fully 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, making it concise, but it lacks structure. It does not front-load key information or present content in an organized way.
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 13 parameters, no output schema, and no annotations, the description is insufficient for an agent to invoke the tool correctly. It omits details about return values, required parameters, and response handling.
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 low (46%), yet the description adds no additional meaning to any parameter. The tool has 13 parameters, but the description does not clarify their semantics beyond what is in 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 that the tool creates a voice-first form link to collect answers and pipe responses back to the agent. However, it does not distinguish itself from sibling tools like create_ask or create_feedback_form.
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 such as create_ask or create_feedback_form. The description lacks any context about prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_responsesGet Superforms ResponsesCInspect
Fetch persisted raw responses for a Superforms ask. This is the MCP equivalent of the HTTP bridge answers endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| askId | Yes | ||
| since | No | ||
| agentToken | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must bear the burden. It states 'fetch persisted raw responses' implying read-only, but does not disclose return format, pagination, rate limits, or authentication prerequisites beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very brief with no wasted words, but it sacrifices necessary detail. It is appropriately front-loaded but incomplete for a tool with no output schema and no annotations.
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 complexity of three parameters and missing annotations, the description is grossly insufficient. It fails to provide parameter semantics, usage context, or behavioral traits beyond the bare minimum.
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 description does not explain any of the three parameters (askId, since, agentToken) despite 0% schema coverage. The agent cannot infer their meaning or formats from the description alone.
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 identifies the action ('Fetch') and the resource ('persisted raw responses for a Superforms ask'), distinguishing it from sibling tools that deal with creation or listing of asks.
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_asks' or 'watch_ask'. The analogy to an HTTP bridge endpoint is not sufficient to inform usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
join_creation_sessionJoin Superforms Creation SessionAInspect
Join a Superforms homepage creation handoff session before creating the real form. Pass agentName with the client name, such as Codex, Claude Code, Claude, ChatGPT, or Cursor.
| Name | Required | Description | Default |
|---|---|---|---|
| agentName | No | ||
| creationSessionUrl | Yes |
Tool Definition Quality
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 describes the action as 'join', implying a non-destructive operation, but does not mention side effects, authentication needs, rate limits, or what happens after joining. This is insufficient for a tool with no 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 concise with two sentences, no fluff. The most critical information (action, resource, usage context) is 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?
For a simple join tool with no output schema, the description provides workflow context ('before creating the real form') and a useful parameter hint. However, it does not explain what the session is, how joining works, or what to do after, leaving some gaps in 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?
The schema has 2 parameters with 0% description coverage. The description adds significant meaning for agentName by specifying it should be a client name and providing examples. However, it gives no additional info for creationSessionUrl, leaving its purpose and format unclear. This is adequate but incomplete.
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 (join) and resource (Superforms homepage creation handoff session), and provides context ('before creating the real form'). It distinguishes itself from sibling tools, which are in a different domain (asks/responses).
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 gives explicit context on when to use ('before creating the real form') and provides a concrete usage hint for the agentName parameter. However, no explicit when-not-to-use or alternative tools are mentioned, though sibling tools are unrelated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_asksList Superforms AsksBInspect
List recent asks for a provided private agent token.
| Name | Required | Description | Default |
|---|---|---|---|
| agentToken | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior fully. It only says 'List recent asks' but does not define 'recent', mention pagination, rate limits, or confirm read-only nature. The return format is not described.
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, concise and front-loaded with the verb 'List'. Every word serves a purpose with no 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 no output schema, no annotations, and minimal parameter info, the description is incomplete. It misses important operational details like response structure, error handling, and token usage, making it insufficient for reliable tool 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?
The sole parameter 'agentToken' has 0% schema description coverage. The description mentions it as a 'private agent token' but does not explain its format, origin, or constraints, leaving the agent with insufficient 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 action ('List') and the resource ('asks') with the specific context of providing a private agent token. It distinguishes from sibling tools like create_ask and get_responses, which are different 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 provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites, exclusions, or context for the agent token. Sibling tools exist but no differentiation is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_creation_sessionUpdate Superforms DraftBInspect
Update a homepage creation handoff draft with the current form title and questions before the final answer link is created.
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | ||
| questions | No | Current draft questions to show in the live form preview. | |
| creationSessionUrl | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'update' without clarifying side effects (e.g., overwrite behavior, permission needs, or state conditions). This is insufficient for a mutation 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 one sentence with no redundancy. It efficiently conveys the core action, though it could be slightly more readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should cover return values, prerequisites (e.g., how to obtain the creation session URL), and post-update state. It does not, leaving significant gaps.
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 low (33%), but the description adds context that 'title' is the form title and 'questions' are draft questions for a live preview. However, 'creationSessionUrl' is not explained beyond being required.
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 updates a homepage creation handoff draft with title and questions, using a specific verb and resource. However, it does not explicitly distinguish itself from sibling tools like 'create_ask' which may be related to the same 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?
Implied usage context ('before the final answer link is created') gives a temporal constraint, but no explicit guidance on when to use versus alternatives or when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
watch_askWatch Superforms AskBInspect
Check whether a Superforms ask has responses. Use get_responses for repeat polling; the HTTP bridge also exposes an SSE stream endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| askId | No | ||
| agentToken | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description offers minimal behavioral detail. It does not state whether the tool is read-only, has side effects, or any rate limits or authentication requirements beyond the agentToken. The brief description lacks necessary behavioral disclosure.
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 very concise (two sentences) but at the expense of essential details. It effectively front-loads the purpose and alternatives, but parameter information is entirely missing, making it less useful than it could be.
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 complexity (3 parameters, no output schema), the description is incomplete. It lacks information on return value, parameter meanings, and behavioral traits. The usage guidelines help but do not compensate for the 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?
The input schema has 3 parameters with 0% description coverage, and the tool description does not explain any of them (url, askId, agentToken). This is a critical gap as the description fails to add meaning beyond the parameter names.
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 purpose: checking whether a Superforms ask has responses. The verb 'check' and resource 'ask' are specific, and it differentiates from sibling tool 'get_responses' which is for polling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises when not to use this tool: 'Use get_responses for repeat polling; the HTTP bridge also exposes an SSE stream endpoint.' This provides clear context and alternatives.
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.
Discussions
No comments yet. Be the first to start the discussion!