ArcadeOps Public Discovery
Server Details
Read-only ArcadeOps discovery for developer docs, OAuth, OpenAPI and synthetic sandbox.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
3 toolsarcadeops_discoverDécouvrir ArcadeOpsARead-onlyIdempotentInspect
Retourne les ressources publiques ArcadeOps, le guide OAuth et l'adresse du MCP métier protégé. Aucune donnée privée n'est lue.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint, idempotentHint, and destructiveHint already present, the annotations carry the safety profile. The description adds useful context: it returns only public resources, includes the OAuth guide and protected MCP address, and explicitly states no private data is read.
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 short sentences with no filler. The primary result is front-loaded, and the important safety guarantee about private data is stated briefly.
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 parameterless discovery tool with strong annotations, the description is sufficiently complete: it states what is returned, that the data is public, and that no private data is accessed. It does not describe the exact output shape, but with no output schema and minimal complexity this is a modest gap.
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 schema provides full coverage trivially. The description does not need to document parameters, and it appropriately implies no input is 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 names a specific verb ('Retourne') and concrete resource categories: public ArcadeOps resources, the OAuth guide, and the protected business MCP address. It is clearly distinct from the sibling document retrieval/search tools, though it does not explicitly name them as alternatives.
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: use this tool to obtain public ArcadeOps resources, the OAuth guide, or the protected MCP address. However, it gives no explicit when-to-use or when-not-to-use guidance relative to arcadeops_get_document or arcadeops_search_docs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
arcadeops_get_documentRésoudre un document ArcadeOpsARead-onlyIdempotentInspect
Retourne le lien canonique et le type MIME d’un document public ArcadeOps identifié.
| Name | Required | Description | Default |
|---|---|---|---|
| document | Yes | Identifiant stable du document public à ouvrir. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already provide read-only, idempotent, and non-destructive hints. The description adds useful behavioral context beyond those hints by specifying that the document is public, and that the result is a canonical link plus MIME type, which tells the agent what kind of operation and response to expect.
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 concise, front-loaded sentence with no filler or repeated information from the schema. It immediately communicates what the tool returns and for what kind of input.
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, read-only lookup tool with annotations covering safety and idempotence, the description is mostly complete: it identifies the input and the output. It does not mention error behavior or explicitly point to sibling tools, but this is a low-complexity tool, so those are minor 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 100%: the single 'document' parameter is fully described as a stable identifier of a public document, and its enum lists valid values. The description does not add much beyond that, but the schema already does the necessary work, so the 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 states a specific verb ('Retourne' / returns) and a specific resource (a public ArcadeOps document), and it names the exact outputs: canonical link and MIME type. The word 'identifié' signals this is a get-by-identifier operation, which distinguishes it from the sibling discover and search tools.
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 clearly implies the tool is for a specific, already-known document ('un document public ArcadeOps identifié'), which is the right mental model for choosing this tool over arcadeops_discover or arcadeops_search_docs. However, it does not explicitly name those alternatives or state 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.
arcadeops_search_docsRechercher la documentation ArcadeOpsARead-onlyIdempotentInspect
Recherche par nom et description dans le catalogue public ArcadeOps. Aucun contenu privé ni appel réseau secondaire.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Termes recherchés, par exemple OAuth, OpenAPI, CLI ou sandbox. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, idempotent, non-destructive), the description adds two behavioral details: the search covers only public content and no secondary network call is made. This gives useful context about side effects and scope without contradicting the 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?
Two short, purposeful sentences with no filler. The primary function is stated first, followed by relevant constraints, making it easy for an agent to parse quickly.
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 single-parameter search tool with rich annotations, the description is nearly complete: it states what is searched, the public scope, and the lack of network side effects. It does not describe the return format, but the tool name and absence of an output schema make the return semantics reasonably inferable.
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 already documents the single 'query' parameter fully with examples. The description adds semantic meaning by stating that the query searches both name and description fields, which is not explicit 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 a specific action: searching by name and description in the public ArcadeOps catalog. It distinguishes the resource and scope, but does not explicitly contrast itself with sibling tools like arcadeops_discover or arcadeops_get_document.
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 when to use the tool (for searching public documentation) and adds a boundary (no private content), but it does not provide explicit guidance on when to prefer this over its siblings or when not to use it.
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.
3 tool updates
- First observed
arcadeops_discover - First observed
arcadeops_get_document - First observed
arcadeops_search_docs
Frequently Asked Questions
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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_..."
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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.
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Feature your server to boost visibility and reach more users
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Claim ownership of the server listing
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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
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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
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Discussions
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TDQS
Each tool has a clearly distinct role: discover provides the top-level public resources and endpoints, search_docs queries the catalog, and get_document resolves a specific document's canonical link and MIME type. There is no meaningful overlap or ambiguity between them.
All tool names share the arcadeops_ prefix and use snake_case, with a consistent verb-based style. The only minor inconsistency is that discover lacks an explicit object noun while get_document and search_docs both include one.
Three tools is well-scoped for a public discovery server: one for overview/discovery, one for searching the catalog, and one for retrieving a specific document's metadata. Each tool earns its place without redundancy.
The tool set covers the core discovery workflow: discover available resources, search the public catalog, and resolve a specific document link. A minor gap is the lack of a direct list-all-documents endpoint, but search by name and description addresses most practical discovery needs.