Natural-language search over 8,900+ Max for Live devices for Ableton Live. Fuzzy full-text plus type, license, popularity and date filters.
Get full details for one device by its numeric id (from search_devices results).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Device id. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description mentions it retrieves details but doesn't disclose behavioral traits like permissions or side effects. Adequate for a simple read 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?
Single sentence with no wasted words; efficiently conveys purpose and source.
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 a single parameter and no output schema, description covers what the tool does and where the input comes from; could mention output structure but not required.
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 covers the parameter with full description; description adds context that the id comes from search_devices results, enhancing meaning beyond 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?
Description clearly states verb 'Get', resource 'full details for one device', and specifies the id source from search_devices results, distinguishing it from sibling 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?
Explicitly indicates to use after search_devices to retrieve full details, but no explicit when-not-to-use or alternatives beyond siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the valid values for the type, license and sort filters of search_devices.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states that it 'list the valid values,' but with no annotations provided, it fails to disclose any behavioral traits such as return format, pagination, authorization requirements, or side effects. For a listing tool, additional context (e.g., whether it requires network access or is fast) would be helpful.
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 directly states the tool's function without any extraneous words. It is front-loaded and efficient, every word 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?
Given the simplicity of the tool (no parameters, no output schema), the description is somewhat complete but lacks details on the output format or examples. It could be more helpful by mentioning the structure of the returned values (e.g., lists of strings).
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?
With zero parameters and 100% schema description coverage, the baseline is 4. The description adds no parameter information because none exist, but this is acceptable.
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: 'List the valid values for the type, license and sort filters of search_devices.' It specifies the verb (List) and the resource (valid filter values), and it distinguishes itself from sibling tools (get_device, search_devices) by focusing on filter metadata rather than device data or search execution.
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 that this tool should be used to obtain filter values before calling search_devices, but it does not explicitly state when to use it or provide alternatives. It lacks guidance on prerequisites or when not to use it, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search ~8,900 Max for Live devices for Ableton Live. Fuzzy full-text match (title/author/description, identical to max4.live) plus filters. Compose for natural language, e.g. "popular free MIDI devices from the last 2 weeks" -> type=[MIDI Effect,MIDI Generator,MIDI Transformation], license=[free], sort=downloads, added_after=.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Default relevance (Fuse ranking with a query, else newest). | |
| type | No | Device types to include. | |
| limit | No | Max results (default 20). | |
| query | No | Free-text fuzzy search (name, author, keyword). Omit to browse by filters only. | |
| license | No | License buckets. free=freeware, commercial=paid, cc=any Creative Commons. For 'free to use' pass [free, cc]. | |
| added_after | No | ISO date (YYYY-MM-DD). Only devices added on/after this date. | |
| min_downloads | No | Minimum download count. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses fuzzy full-text matching (identical to max4.live) and filter behavior. Read-only nature is implied but not explicitly stated. Lacks details on response format or error handling, but is informative for a search 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?
Three sentences: first states purpose and scope, second explains matching, third gives a rich example. No redundant words, front-loaded with the most critical 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 7 optional parameters and no output schema, the description covers search scope, matching mechanism, filters, and usage. However, it omits any description of the response format or fields, which would help an agent understand what is returned. Adequate but with a notable 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?
Schema coverage is 100% (all 7 parameters described), so baseline is 3. The description adds value by providing a concrete example translating natural language into parameters (e.g., 'free to use' -> license=[free, cc]), and hints at implicit filter composition.
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 'Search' and resource 'Max for Live devices for Ableton Live', with scope (~8,900 devices). It distinguishes from siblings 'get_device' (single device) and 'list_filters' (filter options) by focusing on search and browse.
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?
Provides a clear usage example ('Compose for natural language') and translates it into parameter values. Implicitly guides when to use this vs. sibling tools (search vs. single device or filter listing), but lacks explicit when-not or alternative guidance.
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.
get_devicelist_filterssearch_devicesClaiming 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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Add one secure layer between your agents and this server.
Each tool has a distinct purpose: searching, retrieving details, and listing filter options. No overlap between them.
All tool names follow the consistent verb_noun snake_case pattern (get_device, list_filters, search_devices).
With 3 tools covering search, detail retrieval, and filter enumeration, the count is appropriate for the scope of browsing a device database.
The tool surface is complete for its intended purpose: search with filters, get details by ID, and discover available filter values. No obvious gaps.