coremodels
Server Details
Schema modeling in JSON, JSON-LD, and other formats with CoreModels platform.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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.
Tool Definition Quality
Average 3.7/5 across 5 of 5 tools scored. Lowest: 2.9/5.
Each tool has a distinct purpose: exporting schema, fetching single/multiple nodes, retrieving project schema definitions, and summarizing project content. No overlap or ambiguity.
All tools are prefixed with 'core_models_' and use snake_case verb phrases. The mix of 'get', 'fetch', and 'export' is a minor inconsistency but the pattern is still clear and predictable.
With 5 tools, the server covers essential operations for a project data querying and export utility. The count feels well-scoped and not overwhelming.
The tools cover fetching, filtering, pagination, schema retrieval, and export. Missing create/update/delete operations, but the server appears focused on querying and export, so the surface is reasonably complete for that purpose.
Available Tools
4 toolsexport_jsonschemaCInspect
Export project data as a JSON Schema string.
| Name | Required | Description | Default |
|---|---|---|---|
| spaceId | No | ||
| rootNodeId | No | Optional root node id; empty/omitted to export without a fixed root. | |
| configTypeId | No | Export profile id used for the JSON Schema export. | |
| graphProjectId | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as side effects, permissions needed, or whether it is read-only. Only states the basic function.
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 conveys the core purpose, but lacks any structural elements like bullet points or sections that could improve readability.
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 4 parameters and no output schema, the description is severely lacking. It does not explain what the JSON Schema string represents, the role of required parameter graphProjectId, or how spaceId is used, leaving the agent with insufficient context.
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 50% (2 of 4 parameters have descriptions). The tool description adds no additional meaning beyond what is in the schema, failing to compensate for undocumented parameters like spaceId and graphProjectId.
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 action 'Export' and the resource 'project data' with the output format 'JSON Schema string', but does not explicitly differentiate from sibling tools like get_project_summary or search_nodes.
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 alternatives; no description of prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_mixins_and_relation_groupsAInspect
Get the project schema: all mixin definitions and all relation-group definitions.
Use this once at the start of a session to discover the IDs needed by other tools (mixinId, columnId, relationGroupId). Returns compact positional arrays - see the "format" field for the layout.
| Name | Required | Description | Default |
|---|---|---|---|
| graphProjectId | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only mentions that returns 'compact positional arrays' and references a 'format' field, but does not disclose idempotency, potential errors, or side effects. For a read-like operation, more detail on what to expect would be beneficial.
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 extremely concise at two sentences, with no unnecessary words. The first sentence states the purpose, and the second provides usage guidance. It is well-structured and front-loaded for quick comprehension.
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 (one parameter, no output schema), the description is reasonably complete. It covers purpose, usage timing, and return format hint. However, it lacks explanation of the parameter and any potential edge cases, leaving room for improvement.
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 one parameter 'graphProjectId' with zero description coverage. The description does not explain what 'graphProjectId' is or how to obtain it, leaving the agent to infer from the pattern. This is a missed opportunity to add semantic value 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 clearly states the tool retrieves mixin definitions and relation-group definitions, which is its primary purpose. It also explains the use case of discovering IDs for other tools, distinguishing it from siblings like 'export_jsonschema' and 'get_project_summary'.
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 explicitly recommends using this tool 'once at the start of a session' to get necessary IDs, providing clear context. However, it does not mention when not to use it or alternative tools, but the guidance is specific and helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_project_summaryAInspect
Labels and IDs of types, elements, and taxonomies in the project. A category is omitted when it has more than 1000 nodes - use search_nodes with the matching nodeType filter to enumerate it.
| Name | Required | Description | Default |
|---|---|---|---|
| graphProjectId | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the omission behavior for large categories, which is a key behavioral trait. No annotations exist, so description carries the burden; it does not mention auth or side effects, but for a read-like tool this is 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?
Two terse sentences, no fluff, front-loaded with purpose then caveat. 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 no output schema, the description states outputs but lacks structural details. The omission rule is well explained. Could be more complete, but sufficient for a summary tool.
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 0% and description does not explain the parameter graphProjectId, leaving the agent to rely solely on the pattern and required field. The description adds no meaning about what value to provide.
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 returns labels and IDs of types, elements, and taxonomies, and distinguishes from search_nodes by noting when to use that alternative.
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 tells when not to use this tool (category with >1000 nodes) and directs to search_nodes, providing clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_nodesAInspect
Search nodes in a CoreModels project. Returns compact positional arrays; the response "format" field describes the layout.
Filters (provide at least one; they combine with AND):
nodeIds: exact id lookup
nodeType: one of Element, Type, Taxonomy, Exemplar, Component, Space, Tag, Mixin
expression: partial substring match on the node label (plain text, no wildcards)
spaceIds: restrict to specific spaces
Optional flags: includeRelations, includeMixins, sortAttr, sortDesc, pageSize.
Pagination:
First call: omit pagingToken.
If the response has a pagingToken, more pages exist. Repeat the same call with that exact token to get the next page.
If the response has no pagingToken, this was the last page.
| Name | Required | Description | Default |
|---|---|---|---|
| nodeIds | No | ||
| nodeType | No | ||
| pageSize | No | ||
| sortAttr | No | ||
| sortDesc | No | ||
| spaceIds | No | ||
| expression | No | Partial substring match against the node label. Plain text only - no wildcards, no regex, no '*', '%', '_' or '?' characters; the literal characters are matched as-is. | |
| pagingToken | No | Pagination token from the previous response. Always use the latest one. | |
| includeMixins | No | ||
| graphProjectId | Yes | ||
| includeRelations | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the read-like behavior (searching), pagination side effects (tokens), and response structure. It does not explicitly state that data is not modified, but this is implied. No contradictions exist.
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 well-organized with clear sections for filters, optional flags, and pagination. Every sentence is informative, and there is no redundancy. The information is front-loaded with the tool's purpose.
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 11 parameters and no output schema, the description covers filters, pagination, and hints at response format (positional arrays). However, it omits explicit mention of the required parameter and does not fully detail the return structure. An agent might need more context to use the response 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?
Only 18% of parameters have descriptions in the schema, so the description compensates by explaining the role of each filter (nodeIds, nodeType, expression, spaceIds) and optional flags (includeRelations, includeMixins, sortAttr, sortDesc, pageSize). However, it fails to mention the required parameter 'graphProjectId', which is a minor gap.
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 starts with a clear verb and resource: 'Search nodes in a CoreModels project.' It also hints at the response format, making the tool's purpose immediately understandable. The sibling tools have entirely different purposes (exporting schema, getting mixins, project summary), so there is no confusion.
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 explicitly states that at least one filter must be provided and that filters combine with AND, listing each filter type. It also provides a detailed pagination protocol. However, it does not explicitly contrast with sibling tools or specify when not to use it, missing the highest standard.
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.
Discussions
No comments yet. Be the first to start the discussion!