Skip to main content
Glama

Update dynamic endpoint

update_dynamic_endpoint

Update a dynamic endpoint's display_name, description, and content_type (metadata only — this does NOT change the workflow binding or cache setting; author those with create_dynamic_endpoint_version, and the slug cannot be changed). This is a WHOLESALE replace: display_name is required and description + content_type are set to exactly what you pass. IMPORTANT: an empty content_type CLEARS it, reverting the endpoint to serving whatever content-type the workflow returns (e.g. a text/html page would start serving as text/plain). So read the current values with get_dynamic_endpoint first and pass all fields you want to keep.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionNoWhat this endpoint serves. Set wholesale — an empty value clears it.
endpoint_idYesThe endpoint id to update.
content_typeNoThe response Content-Type this endpoint serves (e.g. text/html). Set wholesale — an empty value CLEARS it, reverting to the workflow's own content-type. Pass the current value to preserve serving behavior.
display_nameYesHuman-readable name. Required (cannot be blank).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
versionNo
definitionNo
public_urlNo
descriptionYes
endpoint_idYes
content_typeYes
display_nameYes
latest_versionYes
last_published_versionYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description fully discloses the wholesale replace semantics (all provided fields are set exactly), the requirement that display_name cannot be blank, and the critical edge case where an empty content_type clears it and reverts to the workflow's own content-type. It provides an example (text/html → text/plain) to illustrate the consequence. No annotation contradicts this.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

While the description is moderately long, every sentence contributes essential information: scope, alternative tool, replace semantics, empty-content-type caveat, and a usage tip. The structure is logical and free of filler, making it dense but well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides complete operational context for an agent: which fields are affected, which are not, how the tool behaves on partial input, the critical empty-content-type behavior, and a recommended workflow (read first, then pass all fields). It fully equips the agent to call the tool correctly without needing external clarification.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All four parameters are covered by the schema (100% coverage), and the description adds meaning beyond the schema: it explains the wholesale replace behavior for description and content_type, the clearing implication of an empty content_type, and the required/non-blank nature of display_name. This enriches the schema descriptions significantly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Update'), resource ('dynamic endpoint'), and enumerates the affected fields (display_name, description, content_type). It explicitly distinguishes this tool from create_dynamic_endpoint_version for workflow binding/cache changes and notes the slug cannot be changed, making the purpose unmistakable among the sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly directs when to use this tool versus create_dynamic_endpoint_version for other changes, and advises to read current values with get_dynamic_endpoint first to avoid data loss. This is clear, actionable guidance on when and how to use the tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation5/5

Every resource family follows the same verb+noun pattern and each tool name uniquely identifies a resource-action pair (create_app vs create_app_version vs update_app vs publish_app). Closest overlaps like analyze_resource vs get_resource_graph and patch_datafile vs update_datafile are explicitly differentiated by their descriptions, so misselection risk is low despite the scale.

Naming Consistency5/5

Names are almost uniformly verb_noun snake_case with a consistent lifecycle vocabulary: create/get/update/delete/list/publish/unpublish/version. Minor outliers like whoami and run_schedule_now are idiomatic and do not break the predictability of the set.

Tool Count1/5

At 93 tools this far exceeds the calibration's 50+ extreme-mismatch case. The count is inflated by repeating create/get/update/delete/version/publish/unpublish across ten resource families; even though each family is systematic, the combined surface is very hard for an agent to navigate and keep in context.

Completeness4/5

Core CRUD/publish/version lifecycles are present for apps, workflows, endpoints, schedules, schemas, datafiles, and api templates, and dependency analysis is well covered. However, secret creation/updating, asset upload, custom-domain deletion, and version-range enumeration for several resource types are absent or left to the external dashboard, so agents hit a few manual dead ends.

Resources