Read-only MCP for Electrik Slate: Blade component docs, blocks gallery, source, and llms.txt.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
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.
Average 3.7/5 across 5 of 6 tools scored. Lowest: 3.1/5.
Tools are mostly distinct: component docs vs. source vs. general docs vs. index vs. lists are clearly different. Minor overlap: get_component_docs and get_docs_page both fetch docs markdown, but one is specific to components, the other to page paths, so confusion is low risk.
All tools follow a consistent verb_noun pattern: get_*, list_* with clear noun targets (component_docs, component_source, docs_page, llms_index, blocks, components). The pattern is uniform and predictable.
With 6 tools, the server is well-scoped for a documentation server. The count is appropriate; it covers fetching docs, source, index, and listing components/blocks, without excess. Could argue a couple more might be useful (e.g., search), but it earns a high score.
The server covers documentation and source retrieval, plus listing of components and blocks, but lacks a search tool and lacks update/write operations (though that may be out of scope for a read-only docs server). Some common docs operations like searching or fetching versioned docs are missing, so it's not fully complete.
get_component_docsAInspectFetch markdown documentation for a Slate component (e.g. button, dialog, input).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Component slug, e.g. button, alert-dialog, dark-mode-toggle |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that it fetches markdown documentation (a read operation), but does not mention error behavior (e.g., missing component), rate limits, or other constraints. It adds only a minimal behavioral profile.
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, front-loaded with the key action and resource, and includes a relevant example list. No wasted words.
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 fetch tool, the description adequately covers purpose and parameter. No output schema exists, but the return type (markdown docs) is stated. It lacks error-handling or edge-case notes, but the simplicity of the tool keeps it mostly complete.
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% and the parameter 'name' is well-documented with examples. The description repeats the same examples (button, dialog, input) without adding new meaning beyond the schema. 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 the verb 'Fetch' and the resource 'markdown documentation for a Slate component'. It distinguishes itself from siblings like get_component_source (source code) and get_docs_page (generic docs) by specifying the component doc target with examples.
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 (use for Slate component docs) but does not explicitly contrast with sibling tools or state when not to use. It implies usage by mentioning component names, but lacks explicit alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_component_sourceAInspectFetch the primary Blade source for a Slate component from the 3.x GitHub branch.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Component slug, e.g. button, dialog, toaster |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions fetching from a specific branch, but does not disclose output format, error behavior, or potential network/rate-limit considerations. Some context is added, 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?
A single, front-loaded sentence that immediately conveys the action, target, and branch. Every word earns its place with no unnecessary filler.
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 is sufficiently complete. It specifies what is fetched and from where, which is enough to guide invocation.
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 fully describes the single parameter 'name' with examples. The description adds no additional semantic detail beyond what is in the schema, so baseline 3 applies.
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 'Fetch' and clearly identifies the resource: 'primary Blade source for a Slate component from the 3.x GitHub branch.' This distinguishes it from sibling tools like get_component_docs and list_components.
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 context of fetching source is clear, but there is no explicit guidance on when to use this tool instead of get_component_docs or others. The distinction is implied by the term 'source' but not spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_docs_pageInspectFetch a docs markdown page by path (e.g. getting-started/installation, livewire, ai).
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Docs path without leading docs/, e.g. getting-started/installation or design-tokens |
get_llms_indexBInspectFetch https://slate.electrik.dev/llms.txt — the curated AI index for Slate.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral transparency burden. Although 'Fetch' implies a read-only GET operation, it does not explicitly state side-effect freedom, potential errors, rate limits, or the nature of the response. The description lacks details about what the tool actually does beyond the URL.
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 communicates the essential action and resource. There is no fluff or redundancy, making it highly efficient.
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 is brief and mentions that the resource is a curated AI index for Slate, but it lacks context about the index's purpose, content structure, or expected output. Since there is no output schema, the description should offer more insight into what the tool returns, which it does not. This leaves some gaps in completeness.
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 fully covers parameter semantics. The description adds no parameter-related information, but none is needed. According to the baseline rule for 0 parameters, the score is 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 it fetches a specific URL and identifies it as a curated AI index for Slate. It distinguishes from sibling tools that focus on components or docs. However, it does not explain what 'Slate' is, leaving some ambiguity about the resource's context.
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 alternatives. It does not mention scenarios where fetching the index is preferred, nor does it indicate any prerequisites or fallback options. This leaves the agent without clear selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_blocksBInspectList Slate docs-site blocks (copy-ready Blade sections).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output is 'copy-ready Blade sections' but lacks details about whether it returns a list of block names, full content, or pagination. This is insufficient for a tool with no other behavioral hints.
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, brief sentence that gets straight to the point, with no unnecessary verbiage. It could be slightly more descriptive, but it is appropriately concise for its 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?
Given the tool's simplicity (no parameters, no output schema), the description is mostly adequate, but the lack of what 'blocks' means or how they are returned (e.g., just names or full code) leaves some ambiguity. It is a minimal viable description, but not fully complete.
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 there is nothing for the description to explain. The schema is trivial, and the description adds no parameter-related ambiguity, thus a high score is warranted.
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 lists Slate docs-site blocks, and provides a hint of the content ('copy-ready Blade sections'). It is distinct from siblings like list_components, though it doesn't explicitly differentiate itself.
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 on when to use this tool versus siblings. Without context, an agent might confuse it with list_components. There is no mention of exclusions or alternatives, leaving usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_componentsAInspectList shipped Electrik Slate Blade components with docs URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions 'with docs URLs' which implies the output includes URLs, but it does not disclose other behaviors like read-only safety, pagination, or whether internal components are excluded. For a simple list tool, this is minimal but adequate.
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?
One sentence, front-loaded verb, zero filler. Perfectly concise and to the point.
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 fully covers its purpose and the key output detail (docs URLs). It is a simple list operation and nothing more is needed.
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?
Tool has zero parameters, and schema coverage is 100% (trivially). The description does not need to explain parameters, and the baseline for 0 params is 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?
Description clearly states verb 'List' and resource 'shipped Electrik Slate Blade components' with an additional detail about docs URLs. This distinguishes it from siblings like get_component_docs and get_component_source, which focus on individual components rather than a list.
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 purpose implies when to use it (to obtain a list of all components), which is clear context. However, it does not explicitly mention when not to use it or suggest alternatives, such as using get_component_docs for detailed documentation of a specific component.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$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.
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
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.
No comments yet. Be the first to start the discussion!
