haunt
Server Details
Turn any public URL into clean JSON/markdown for AI agents. Free 1,000 credits/mo, no card.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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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 4.1/5 across 3 of 3 tools scored. Lowest: 3.4/5.
Each tool has a clearly distinct purpose: 'extract' performs real extraction, 'get_usage' retrieves plan and quota information, and 'try_demo_extract' returns a fixed sample without any API call. There is no overlap in functionality.
Tool names start with verbs but follow slightly different patterns: 'extract' is a bare verb, 'get_usage' follows verb_noun, and 'try_demo_extract' is more complex. The naming is mostly consistent and readable, with minor deviation.
With 3 tools covering core extraction, usage monitoring, and a demo mode, the count is well-scoped for a focused API service. Each tool earns its place without excess or deficiency.
The tool set covers the essential operations: extraction, usage tracking, and a demo for testing. Minor gaps like listing or canceling extractions exist but are acceptable for a minimal API surface.
Available Tools
3 toolsextractBInspect
Extract structured JSON from a permitted public URL using Haunt API. Requires Authorization: Bearer or X-API-Key.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | http:// or https:// URL to extract from | |
| prompt | Yes | Plain-English fields to extract |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses authentication requirements (Bearer or X-API-Key) which is valuable since no annotations are provided. However, lacks details on rate limits, error handling, or behavior when URL is not permitted, leaving gaps for an agent.
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, front-loaded with action. Every word serves a purpose; 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?
For a simple tool with two parameters and no output schema, the description adequately covers the core action and authentication. It could mention the return format more explicitly, but 'structured JSON' suffices.
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%, so baseline is 3. The description does not add additional meaning beyond the schema; it repeats the prompt concept but provides no new insights.
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 tool extracts structured JSON from a permitted public URL using the Haunt API. The verb and resource are specific, distinguishing it from get_usage and try_demo_extract, but does not elaborate on the nature of extraction.
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 alternatives. The mention of 'permitted public URL' hints at constraints, but there is no direct comparison with sibling tools or when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_usageAInspect
Return current Haunt plan, monthly limit, and remaining successful requests. Requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 discloses the API key requirement but does not mention other behavioral aspects like idempotency, rate limits, or data freshness. A 3 is appropriate because it adds some context but leaves gaps.
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 plus an additional requirement statement, with no unnecessary words. Every part adds 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?
For a tool with no output schema, the description covers the main return values (plan, limit, remaining requests). However, it could mention data types or example formats for completeness. Still, it provides solid 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 tool has zero parameters and the schema description coverage is 100%. Per calibration, 0 parameters results in a baseline of 4. The description correctly does not add parameter info since none 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 uses a specific verb ('Return') and identifies the exact data returned: current Haunt plan, monthly limit, and remaining successful requests. This clearly distinguishes from sibling tools like 'extract' and 'try_demo_extract', which are focused on extraction.
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 states a key usage requirement: 'Requires an API key.' It does not mention when to use this tool versus alternatives, but alternatives are different enough that this is not critical.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
try_demo_extractAInspect
Return fixed sample Haunt extraction JSON. No signup, API key, remote fetch, provider call, or quota usage.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description fully discloses all behavioral traits: returns fixed sample, no side effects, no external calls, no quota usage. Complete 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?
Single sentence, no wasted words, front-loaded with key action. Every clause 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?
Tool has no parameters and no output schema; description fully captures purpose, behavior, and usage constraints. Complete 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?
No parameters; schema coverage 100% (empty). Description adds no parameter info, but baseline for zero params is 4. No further detail 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?
Description clearly states verb 'Return' and resource 'fixed sample Haunt extraction JSON', distinguishing it from siblings (real extraction vs sample). No 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?
Explicitly lists constraints (no signup, API key, etc.), indicating use for testing/demo. Does not explicitly contrast with siblings but the context is clear.
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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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
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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.
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