api-diff-monitor
Server Details
Cloudflare Workers MCP server: api-diff-monitor
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
6 toolscompare_snapshotsAInspect
Fetch a registered endpoint and compare against its last snapshot to detect schema changes. Or compare two inline JSON objects directly.
| Name | Required | Description | Default |
|---|---|---|---|
| save | No | Save snapshot and diff to history (default: true) | |
| snapshot_a | No | Inline "before" JSON (omit endpoint_id for direct comparison) | |
| snapshot_b | No | Inline "after" JSON (omit endpoint_id for direct comparison) | |
| endpoint_id | No | ID of a registered endpoint to fetch and compare |
TDQS
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 side effects. It mentions 'fetch' (network call) and 'compare' (read operation) but omits the default side effect of saving to history (save parameter defaults to true). This is a significant transparency gap for a tool that persists state by default.
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, front-loaded with the primary action, and wastes no words. Each sentence adds a distinct usage scenario, making it both concise and informative.
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 tool has 4 optional parameters and no output schema, yet the description does not explain what the tool returns or how it handles ambiguous cases (e.g., providing both endpoint_id and snapshot_a/b). It covers the core purpose but leaves out return value details and edge-case behavior, making it only minimally complete for a tool with no annotations.
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%, so the baseline is 3. The description adds semantic value by explaining the two parameter modes (endpoint_id vs snapshot_a/snapshot_b), which clarifies how the parameters interact and when each is appropriate. This goes beyond simple property descriptions and earns a 4.
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 primary function: 'Fetch a registered endpoint and compare against its last snapshot to detect schema changes' and immediately provides an alternative use case: 'compare two inline JSON objects directly.' This distinguishes it from sibling tools like register_endpoint or detect_breaking_changes by focusing on the comparison action.
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 clear context for when to use each mode: use endpoint_id for registered endpoints, or snapshot_a/snapshot_b for inline comparison. It doesn't explicitly name alternatives like detect_breaking_changes, but the two distinct usage patterns effectively guide the agent. Missing explicit exclusions or 'when not to use' guidance, preventing a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_endpointAInspect
Remove a monitored endpoint and all its snapshots and diff history.
| Name | Required | Description | Default |
|---|---|---|---|
| endpoint_id | Yes | Endpoint ID to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly discloses that the operation is destructive and cascades to 'all its snapshots and diff history', which is critical behavioral context. It does not mention irreversibility or permission requirements, but the key side effects are clearly stated.
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 that front-loads the action and scope without unnecessary words. Every word earns its place, and the structure is immediately comprehensible.
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 one-parameter delete operation with no output schema, the description is adequately complete. It explains what is deleted, including the cascading effect on snapshots and diff history. It could mention error behavior or idempotency, but those are minor gaps given 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?
The schema already provides 100% coverage of the parameter meaning with 'Endpoint ID to delete'. The description adds no additional parameter-level detail, so the baseline score of 3 applies; the schema carries the semantic weight.
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 'remove' and identifies the resource as 'a monitored endpoint' with explicit scope ('all its snapshots and diff history'). This clearly distinguishes it from sibling tools like compare_snapshots, get_diff_history, and register_endpoint, which serve different purposes.
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 deleting an endpoint, but provides no explicit guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It does not mention that this is the inverse of register_endpoint or that it should be used when permanent removal is intended.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_breaking_changesBInspect
Check if a registered endpoint has had any breaking changes (removed fields or type changes).
| Name | Required | Description | Default |
|---|---|---|---|
| endpoint_id | Yes | Endpoint ID |
TDQS
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 defines breaking changes but does not mention whether the operation is read-only, what happens if the endpoint does not exist, or what the return value looks like. The description implies a non-mutating check but does not explicitly confirm safety 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?
The description is a single, focused sentence that defines the tool's purpose and even clarifies what counts as a breaking change. There is no waste or redundancy, making it highly concise and appropriately 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?
For a simple one-parameter tool with no output schema and no annotations, the description provides a decent baseline but lacks details on the comparison baseline (e.g., against what?) and edge-case behavior. It is minimally complete but leaves some contextual gaps that an agent might need to infer.
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 100% description coverage for the single parameter endpoint_id, with a basic description 'Endpoint ID'. The tool description adds no additional meaning or constraints beyond the schema, so the 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 a specific action ('Check') on a specific resource ('a registered endpoint') and defines the scope as 'breaking changes (removed fields or type changes)'. This distinguishes it from sibling tools like compare_snapshots or get_diff_history, which focus on different aspects of endpoint monitoring.
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 the tool is used for checking registered endpoints but provides no explicit guidance on when to use this tool versus alternatives like compare_snapshots or get_diff_history. There are no when-to-use or when-not-to-use instructions, leaving the decision to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_diff_historyAInspect
Retrieve the schema diff history for a registered endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max diffs to return (default: 20, max: 50) | |
| endpoint_id | Yes | Endpoint ID |
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. 'Retrieve' implies a non-mutating read, and 'for a registered endpoint' suggests a precondition. However, the description does not disclose details like ordering, error behavior, or what the diff history entries contain. It's minimal but not misleading, scoring at the 'implied usage' level.
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 states the action and target without unnecessary words. It is front-loaded and every word 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 simple read tool with full schema coverage, the description is adequate but leaves gaps. There is no output schema, so the agent is not told the return format or what a 'diff history' entry looks like. Error handling and ordering are also unspecified. Given the simplicity of the tool, this is a minimally viable description but not rich.
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%, with both 'endpoint_id' and 'limit' having descriptions. The tool description itself adds no parameter-level information beyond what the schema already provides, but the schema fully covers the meaning. 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 uses a specific verb 'retrieve' combined with a resource 'schema diff history' and a qualifier 'for a registered endpoint'. This clearly distinguishes it from sibling tools like compare_snapshots (which compares snapshots) and detect_breaking_changes (which analyzes changes).
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 clear context: this is the tool for getting schema diff history for a registered endpoint. It doesn't explicitly name alternatives or say when not to use it, but the scope is evident from the qualifier 'for a registered endpoint', which implies it's not for unregistered endpoints or for comparing snapshots.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_monitored_endpointsAInspect
List all registered API endpoints being monitored.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clarifies that the operation lists all *monitored* endpoints, which is a specific behavioral scope. The verb 'List' implies a read-only operation with no side effects, which is sufficient transparency 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 a single, direct sentence with no wasteful content. It front-loads the action and resource immediately.
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 parameters and no output schema, the description provides a clear high-level overview. However, it does not specify the return format or any additional behavior, which is a minor gap given the absence of annotations and output schema.
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, so the description does not need to explain parameter behavior. The baseline of 4 applies here.
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 'List' and identifies the resource as 'registered API endpoints being monitored'. This clearly distinguishes it from sibling tools like register_endpoint, delete_endpoint, and detect_breaking_changes, which 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 implies usage when you need to view all monitored endpoints, but it does not explicitly state when to prefer this over alternatives or provide any exclusions. There is no mention of use cases or contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
register_endpointBInspect
Register an API endpoint to monitor for schema changes. Provide name, url, and optionally method/headers/description.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | API URL to monitor | |
| body | No | Request body (for POST/PUT) | |
| name | Yes | Identifier for this endpoint | |
| method | No | HTTP method (default: GET) | |
| headers | No | Request headers | |
| description | No | Optional description |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry behavioral disclosure. It only states the registration action and monitoring purpose, omitting side effects, idempotency, authentication needs, duplicate handling, or response details. This is 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 a single 15-word sentence, front-loaded with the core purpose and followed by compact parameter guidance. There is no filler 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, nested headers, and no annotations or output schema, the description leaves significant gaps. It does not explain what happens after registration, whether duplicates are handled, or what the tool returns.
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%, meeting the baseline. The description highlights name, url, method, headers, and description but omits the 'body' parameter, adding little semantic value beyond what the schema already provides.
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 and resource ('Register an API endpoint') and clarifies the purpose ('to monitor for schema changes'). This clearly distinguishes it from sibling tools like compare_snapshots or delete_endpoint.
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 you want to add an endpoint to monitoring) but provides no explicit when-to-use guidance or alternative comparisons. It offers parameter invocation hints ('Provide name, url, and optionally...') rather than context for tool selection.
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.
5 tool updates
- Changed
compare_snapshots4 fields changed- changed
Input schema / properties / endpoint_id / descriptionPrevious value: -"비교할 등록 엔드포인트 ID (직접 비교 시 생략)"New value: +"ID of a registered endpoint to fetch and compare" - changed
Input schema / properties / save / descriptionPrevious value: -"스냅샷 및 diff를 KV에 저장 여부 (기본: true)"New value: +"Save snapshot and diff to history (default: true)" - changed
Input schema / properties / snapshot_a / descriptionPrevious value: -"직접 비교할 첫 번째 JSON 객체"New value: +"Inline \"before\" JSON (omit endpoint_id for direct comparison)" - changed
Input schema / properties / snapshot_b / descriptionPrevious value: -"직접 비교할 두 번째 JSON 객체"New value: +"Inline \"after\" JSON (omit endpoint_id for direct comparison)"
- Added
delete_endpoint - Changed
detect_breaking_changes1 field changed- changed
Input schema / properties / endpoint_id / descriptionPrevious value: -"엔드포인트 ID"New value: +"Endpoint ID"
- Changed
get_diff_history2 fields changed- changed
Input schema / properties / endpoint_id / descriptionPrevious value: -"엔드포인트 ID"New value: +"Endpoint ID" - changed
Input schema / properties / limit / descriptionPrevious value: -"반환할 최대 diff 수 (기본: 20, 최대: 50)"New value: +"Max diffs to return (default: 20, max: 50)"
- Changed
register_endpoint6 fields changed- changed
Input schema / properties / body / descriptionPrevious value: -"요청 바디 (POST/PUT 등)"New value: +"Request body (for POST/PUT)" - changed
Input schema / properties / description / descriptionPrevious value: -"엔드포인트 설명"New value: +"Optional description" - changed
Input schema / properties / headers / descriptionPrevious value: -"요청 헤더 (키-값 객체)"New value: +"Request headers" - changed
Input schema / properties / method / descriptionPrevious value: -"HTTP 메서드 (기본: GET)"New value: +"HTTP method (default: GET)" - changed
Input schema / properties / name / descriptionPrevious value: -"엔드포인트 식별 이름"New value: +"Identifier for this endpoint" - changed
Input schema / properties / url / descriptionPrevious value: -"모니터링할 API URL"New value: +"API URL to monitor"
5 tool updates
- First observed
compare_snapshots - First observed
detect_breaking_changes - First observed
get_diff_history - First observed
list_monitored_endpoints - First observed
register_endpoint
Frequently Asked Questions
Claiming 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 asio.github.acme/serveralso 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.jsonon 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.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Connectors
Cloudflare Workers MCP server: api-changelog-tracker
Cloudflare Workers MCP server: api-schema-drift-detector
Cloudflare Workers MCP server: api-payload-auditor
Cloudflare Workers MCP server: api-flow-analyzer
Related MCP Servers
- AlicenseNot gradedqualityBmaintenanceMCP server for managing Cloudflare Workers via Cloudflare Artifacts. Enables editing, committing, and deploying worker scripts directly.8MIT
- AlicenseAqualityDmaintenanceMCP server to manage Cloudflare Workers, KV, R2, Pages, DNS, and cache from your IDE.13554MIT
- FlicenseNot gradedqualityBmaintenanceA stateless MCP server on Cloudflare Workers providing a ping tool and a CSV column summarizer, demonstrating the createMcpHandler API.-
- AlicenseNot gradedqualityDmaintenanceEnables creation and deployment of MCP servers on Cloudflare Workers, with local testing and one-command deployment.115MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Each tool has a clearly distinct purpose: CRUD operations for endpoints (register, list, delete) are separate from diff analysis (compare_snapshots, detect_breaking_changes, get_diff_history). Even the two diff-related tools differ in focus: compare_snapshots detects any changes, while detect_breaking_changes specifically flags breaking changes.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., register_endpoint, list_monitored_endpoints, detect_breaking_changes). Verbs are specific and the pattern is predictable throughout.
Six tools is well-scoped for an API diff monitoring server. Each tool covers a distinct aspect of the domain without redundancy, and the count is within the ideal range for coherence.
The tool set covers the core lifecycle of endpoints (register, list, delete) and the primary diff operations (compare, detect breaking, view history). Minor gaps like updating an endpoint or manually triggering a snapshot exist, but the inline comparison option in compare_snapshots provides a workaround for testing changes.