stepcode
Server Details
Read-only MCP access to stepcode.dev's how-to corpus: analysis pages by tool.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
TDQS
The tools are mostly distinct: get_howto_page retrieves detail, list_analysis_families aggregates families, and list_howto_pages/search_howto_pages cover browsing with and without filters. The overlap between list_howto_pages and search_howto_pages (search with no args returns the same result) introduces minor ambiguity, but the descriptions clarify the intended use.
All tool names follow a consistent verb_noun snake_case pattern: get_howto_page, list_analysis_families, list_howto_pages, search_howto_pages. The verbs (get, list, search) clearly reflect the operation, and nouns identify the resource with appropriate singular/plural usage.
Four tools is well-scoped for a read-only content retrieval server. Each tool serves a distinct need without redundancy or bloat, covering the core interactions users would expect: listing, filtering, fetching detail, and exploring families.
The surface fully covers the domain of browsing stepcode.dev's how-to content. It provides list, search, get-by-slug, and family-level aggregation—no obvious missing operations for a read-only content API. Users can discover pages, filter them, retrieve full details, and understand the family structure.
Available Tools
4 toolsget_howto_pageGet one stepcode how-to pageARead-onlyInspect
Get the full howto/v2 contract for one page by slug (from list_howto_pages / search_howto_pages): intro, per-step teach/intent/code, divergence notes, cross-tool links, and grounding.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | How-to page slug, e.g. flight-risk-predict-which-employees-will-resign-in-excel. |
Output Schema
| Name | Required | Description |
|---|---|---|
| page | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the read-only nature is covered. The description adds useful context about what the 'full contract' includes (intro, per-step content, divergence notes, cross-tool links, grounding), but does not go beyond that to disclose rate limits, error behavior, or other operational traits.
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 compact sentence front-loads the primary action and resource, then efficiently enumerates the returned content. There is no filler or repetition of schema details.
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 only one required parameter, a fully documented schema, an output schema, and read-only annotations, the description covers the essential workflow: obtain a slug from list/search, then fetch the full page. Nothing critical is missing.
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 slug parameter already includes a concrete example. The description reinforces that the slug identifies one page and originates from sibling tools, but adds little beyond 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 uses a specific verb ('Get') and resource ('the full howto/v2 contract for one page by slug'), and clearly distinguishes this single-page retrieval tool from the sibling list/search tools by naming them as sources of the slug. An agent can tell exactly what this tool does and what it returns.
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?
It explicitly says the slug comes from list_howto_pages / search_howto_pages, which tells the agent when to use this tool: after finding a page via the sibling tools. It does not state explicit when-not conditions for sibling alternatives, but the context is clear enough for this simple one-parameter tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_analysis_familiesList stepcode's analysis familiesARead-onlyInspect
List the analysis families on stepcode.dev (e.g. flight-risk, diversity-index-EBIT-impact) with the tools each is shown in and how many pages exist for it.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| families | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the operation as read-only and non-destructive. The description adds useful behavioral detail by specifying what the listing includes (tools shown and page counts), which goes beyond the structured 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?
A single well-structured sentence that front-loads the action and resource, includes clarifying examples, and summarizes the output. Every element earns its place with no 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?
For a simple zero-parameter list operation with a read-only annotation and an output schema present, the description provides enough context. It covers what is listed, where it is from, and what is included in the result.
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 parameter semantics are not a burden on the description. The schema fully covers this case, and the description contributes relevant detail about what the result set represents.
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 ('List') and resource ('analysis families on stepcode.dev'), provides concrete examples, and clarifies the output includes associated tools and page counts. This clearly distinguishes it from sibling tools that operate on howto pages.
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 makes the tool's scope obvious but does not explicitly say when to choose it over alternatives or mention exclusions. Usage is implied through the resource type and examples, but no direct comparison to sibling tools is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_howto_pagesList stepcode's how-to pagesARead-onlyInspect
List every published how-to page on stepcode.dev — 36 analysis x tool cells (Excel, Google Sheets, R, Python, SQL, DAX/Power BI) with slug, title, analysis family, tool, vertical and whether the tool's approach diverges from the others.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| pages | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish this is a safe read-only operation. The description adds useful behavioral scope: only published pages, all 36 analysis x tool cells, and the divergence flag. It does not mention ordering or pagination, but the fixed small set and zero parameters make those less critical.
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 dense sentence leads with the verb and resource, then packs the scope and returned fields into a well-organized em-dash clause. 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 no parameters, an output schema available, and annotations covering the safety profile, the description provides the remaining essential context: exactly what the listing contains and its scope. Nothing critical is missing for an agent to invoke this tool correctly.
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 zero parameters and 100% schema description coverage, so there is no parameter burden for the description to carry. No parameter documentation is needed.
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 opens with a specific verb and object: 'List every published how-to page on stepcode.dev.' It then enumerates the exact fields returned, making it clearly distinct from get_howto_page (single page) and search_howto_pages (filtered lookup).
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 this is for full enumeration of all how-to pages, but it does not explicitly state when to choose this tool over search_howto_pages or get_howto_page. No alternatives or exclusion conditions are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_howto_pagesSearch stepcode's how-to pagesARead-onlyInspect
Filter the how-to index by analysis family, tool, vertical, and/or a case-insensitive text query against title + analysis name. All filters are optional and combine with AND; call with no arguments to get every page (same as list_howto_pages).
| Name | Required | Description | Default |
|---|---|---|---|
| tool | No | Tool slug, e.g. excel, sheets, r, python, sql, dax. | |
| query | No | Case-insensitive substring match against title + analysis name. | |
| vertical | No | Vertical slug, e.g. hr. | |
| analysisSlug | No | Analysis family slug, e.g. flight-risk-predict-which-employees-will-resign. |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| pages | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false. The description adds meaningful behavioral details beyond that: case-insensitive substring matching, AND-combination of filters, optional filters, and the equivalence to list_howto_pages when called with no arguments. This is useful operational context not present in 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 sentences with no filler. The primary filtering behavior is stated first, followed by the important AND-combination semantics and the no-argument behavior. Every sentence adds value and the structure is easy to scan.
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 moderate complexity (four optional parameters, zero required), the description is complete: it explains filter combination, optionality, case-insensitivity, and the degenerate no-argument case. The presence of an output schema covers return-value expectations, so no major context is missing.
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%, so every parameter is already documented in the input schema. The description confirms the query behavior (case-insensitive substring against title + analysis name) but does not substantially add meaning 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?
Description states a specific verb ('Filter the how-to index') and names the four filtering dimensions: analysis family, tool, vertical, and text query. It clearly distinguishes this from list_howto_pages by noting that no-argument calls return every page, while also framing itself as the filtering entry point.
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 usage context: all filters are optional, combine with AND, and the no-argument behavior matches list_howto_pages. It does not explicitly enumerate when NOT to use this tool or direct the agent to a sibling for unfiltered listing, but the 'same as list_howto_pages' note provides a useful comparison.
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.
4 tool updates
- First observed
get_howto_page - First observed
list_analysis_families - First observed
list_howto_pages - First observed
search_howto_pages
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
Read-only MCP access to devplane.dev's public pages, FAQ corpus and comparisons.
41Public read-only MCP for products, frameworks, guides, methodology, and blog metadata.
- dataOAuthco.thinair
Read-only PostgreSQL, MySQL, SQL Server access via MCP — 24 dialect-aware hosted tools.
Read-only MCP for the Eco game wiki: search, Markdown pages, and wiki_* lookups. No keys, no writes.
Related MCP Servers
- AlicenseAqualityAmaintenanceTwelve tools combine per-function complexity and branch coverage to rank work and check edited functions against their ceiling. Packets include source, uncovered lines, change-coupled files and near-duplicates. MCP calls can write local caches and metadata; they do not run test suites, edit source or claim work.4121MIT
- AlicenseAqualityCmaintenanceRead-only MCP tools for coding agents to audit deployment targets, detect fabricated code, review backlog, database schema, analytics, ML models, architecture docs, and decision lenses.1119MIT
- AlicenseAqualityCmaintenanceProvides read-only access to iFixit repair guides, device information, repairability scores, categories, search, media, and contributor profiles via MCP tools.8BSD Zero Clause
- AlicenseNot gradedqualityAmaintenanceEnables proof-backed code audit via MCP tools for AST-based code maps, symbol lookup, callers, audit commands, and persistent verdict memory.MIT