Monitor public pages with source URLs, timestamps, hashes, text diffs and signed webhooks. One daily monitor is free for 30 days; the $9, 30-day pass adds five monitors at a 15-minute minimum interval, 15,000 checks and change history. No auto-renewal. Public connection supports preflight and offer tools; obtain a key on the website (POST /v1/keys/free for the free tier) and pass api_key to monitor tools. Public text/HTML/JSON/XML up to 3 MB; no browser rendering or login bypass. Hosted commercial service; engine and source remain private.
Each tool has a clear, distinct purpose: preflight tests a URL, create_monitor sets up monitoring, check_now runs an immediate check, list_changes retrieves receipts, and offer provides pricing. No two tools overlap in functionality, making selection unambiguous.
All tools share the consistent 'fluxproof_' prefix and use snake_case. However, verbs vary in structure—some are verb_noun (create_monitor, list_changes), while others are verb+adverb (check_now) or a single verb/noun (offer, preflight). The pattern is recognizable but not perfectly uniform.
With 5 tools, the server is tightly scoped to the core workflows of testing URLs, creating monitors, running checks, listing evidence, and accessing pricing. Each tool is essential and the count is ideal for the domain.
The tool set covers the main lifecycle: preflight for validation, create_monitor for setup, check_now for immediate verification, and list_changes for historical evidence. Missing operations like updating or deleting monitors are minor gaps since they may be intentionally omitted for a focused service.
Run a monitor now and return a source- and hash-bound change receipt.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | ||
| monitor_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations to clarify side effects, failure modes, authentication requirements, or costs. The description only promises a receipt, leaving important behavioral context implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler or redundant wording. It communicates the core purpose efficiently.
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 omits necessary operational context such as what the receipt contains, how to obtain required values, and what happens when the monitor fails. An agent would need to infer important details.
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 api_key or monitor_id, and the schema provides no descriptions. With 0% parameter coverage, the description fails to add meaningful parameter semantics.
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 ('Run a monitor now') and the expected output ('change receipt'), which distinguishes it from sibling tools like create, list, offer, and preflight.
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 no guidance on when to use this tool versus alternatives, such as on-demand triggers, scheduling, or exclusions. It only states what the tool does, not when it should be selected.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Create a monitor using a buyer-owned FluxProof API key.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| label | No | ||
| api_key | Yes | ||
| watch_terms | No | ||
| webhook_url | No | ||
| interval_minutes | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior, but it only states the creation action. It does not disclose side effects (e.g., does the monitor start polling immediately?), persistence, potential costs associated with a buyer-owned key, failure modes, or what happens on duplicate monitors.
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, tightly worded sentence with the action verb front-loaded. Every word earns its place with no fluff or 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?
With 6 parameters, no output schema, and no annotations, the description leaves substantial gaps: parameter meanings, expected response/return value, required preconditions, error behavior, and post-creation semantics are all unspecified.
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 0% description coverage, so the description must compensate. It only clarifies the api_key parameter ('buyer-owned'), leaving url, label, watch_terms, webhook_url, and interval_minutes entirely unexplained in both the schema and the description.
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 'Create' and the resource 'monitor', making the core action unambiguous. It does not explicitly name sibling tools for differentiation, but 'create' is semantically distinct from check_now, list_changes, offer, and preflight, so an agent can likely infer the right tool.
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 the sibling tools (fluxproof_check_now, fluxproof_list_changes, fluxproof_offer, fluxproof_preflight). There is no mention of prerequisites, sequencing (e.g., run preflight first), or scenarios where this tool is or is not appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List recent evidence receipts for a monitor.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| api_key | Yes | ||
| monitor_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation ('list') but does not explicitly state side effects, safety, or whether it modifies state. With no annotations to clarify, the burden falls on the description, which is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the action and object. It is appropriately sized with no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the operation and the absence of an output schema, the description is adequate for a basic list tool. It does not mention pagination or limit behavior, but these are relatively minor gaps for such a straightforward action.
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 provides parameter names (api_key, monitor_id, limit) and types, but no descriptions. The tool description does not add any meaning beyond the schema, so it relies on self-explanatory names. The coverage is 100%, setting a baseline of 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 action (list) and the resource (recent evidence receipts) with a target (a monitor). While it does not explicitly distinguish from sibling tools, the actions of siblings (check, create, offer, preflight) are sufficiently different to avoid confusion.
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 the alternatives. The description only states what it does, without any contextual triggers or conditions for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return free and paid boundaries and purchase routes without charging.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral detail, but it only says 'without charging', which is unclear and possibly tautological with 'free'. It does not disclose side effects, required permissions, or whether this is a read-only operation.
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 front-loaded with the action, but the phrasing is cryptic. 'Without charging' adds little and may confuse rather than clarify.
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 lacks essential context: what a 'boundary' or 'purchase route' is, what the output looks like, and why a user would call this tool. With no output schema, the description is the only source of expectations, and it is insufficient.
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 zero parameters, so there is no parameter documentation burden. The description does not need to explain parameters, and no parameter-related conflict exists.
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 states a verb ('Return') and an object ('free and paid boundaries and purchase routes'), but the object is opaque and the phrase 'without charging' is ambiguous. It is not clear what 'boundaries' or 'purchase routes' refer to, nor how this tool differs from siblings like 'check_now' or 'preflight'.
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 no guidance on when to use this tool versus the sibling tools. There is no mention of conditions, use cases, or situations where 'offer' is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a public URL and return fetchability, size, final URL, title, and content hash without page content or payment.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose that it does not return page content and requires no payment, and implies a read-only fetch of a public URL. However, it does not explicitly state whether the operation is non-destructive, if any authentication is needed, or what happens on failure (e.g., unreachable URL). This is partially transparent but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently packs the action, outputs, and exclusions. Every word adds value, and there is no fluff or repetition. It is appropriately sized for the tool's simplicity.
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 one parameter and no output schema, the description covers the core: what it returns and what it does not. However, it omits details on failure behavior, return format (e.g., data types of the fields), and any potential limitations (e.g., size limits). These gaps leave an agent somewhat uncertain about edge cases, though the main purpose is clear.
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 0%, so the description must explain the 'url' parameter. It says 'Fetch a public URL', which clarifies that the parameter should be a publicly accessible URL. This adds a constraint not present in the schema (which just says string). However, it does not provide format details, normalization, or error behavior for invalid URLs, so it only partially compensates.
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 ('Fetch a public URL'), the resource (a public URL), and the exact outputs (fetchability, size, final URL, title, content hash) while explicitly excluding page content and payment. This distinguishes it from siblings like fluxproof_check_now or fluxproof_create_monitor, which presumably perform different 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 any guidance on when to use this tool versus the siblings. It never mentions alternatives, conditions, or exclusions. The name 'preflight' implies a preliminary check, but the description itself offers no explicit usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
fluxproof_check_nowfluxproof_create_monitorfluxproof_list_changesfluxproof_offerfluxproof_preflightClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity – fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge – works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge – works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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.
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