kanka-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation4/5
Most tools have clearly distinct purposes (e.g., create vs. update vs. delete, search vs. full text search vs. list). However, kanka_search and kanka_full_text_search could be confused if descriptions are overlooked, and kanka_list_entities overlaps slightly with browse/search capabilities.
Naming Consistency3/5
Tools generally follow a 'kanka_verb_noun' pattern, but 'kanka_posts' and 'kanka_relations' are nouns only, breaking consistency. The use of 'full_text_search' with underscores is fine, but the mix of verbs and bare nouns is noticeable.
Tool Count5/5
With 15 tools, the server covers authentication, campaign management, entity CRUD, posts, relations, search, and schema discovery without feeling bloated. Each tool addresses a distinct need, and the count is appropriate for the domain.
Completeness4/5
The tool surface covers essential CRUD for entities, posts, and relations, plus search and auth. Minor gaps: there is no tool to list entity types or manage campaigns beyond fetching metadata, but these are not critical for typical workflows.
Average 4.2/5 across 15 of 15 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 3 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on May 8, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states 'fetch metadata' implying read-only, but does not disclose any other behavioral traits (e.g., error behavior, response format, restrictions).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 8 words, front-loaded with action and resource. No wasted words, but at the cost of omitting useful context. Appropriate for a simple tool but slightly too terse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description fails to explain what 'metadata' includes or what the return value looks like, leaving the agent with incomplete information for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description mentions 'by id' linking to the parameter, but does not add meaning beyond the schema's explicit 'campaign_id' field. Schema already defines integer with exclusiveMinimum:0.
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 uses specific verb 'fetch' and resource 'metadata for a single campaign by id', clearly distinguishing from sibling 'kanka_list_campaigns' which lists all campaigns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit usage guidance, but the purpose and naming imply use when a single campaign ID is known. The presence of a sibling list tool provides implicit differentiation. Lacks when-not or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions transparent ID resolution but does not disclose if this involves extra API calls, side effects, authentication requirements, or rate limits. It fails to fully inform the agent of the tool's behavior.
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?
The description is two sentences, each serving a purpose: the first states the action, the second explains the ID resolution. No unnecessary words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should cover return format, error handling, or limits for a fetch tool. It lacks these details, making it incomplete for robust usage by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description adds meaning by explaining the dual-ID system and the relationship between entity_type, id, and entity_id. However, it does not describe campaign_id, which is required, leaving a gap in parameter understanding.
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 clearly states 'Fetch a single entity', giving a specific verb and resource. It distinguishes from sibling tools like kanka_list_entities by focusing on fetching one entity. The mention of two ID systems adds specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the two ways to specify the entity (type-scoped id vs global entity_id), giving usage context. However, it does not explicitly say when to use this tool over alternatives like kanka_search or kanka_list_entities, nor does it provide exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions 'fast, server-side' and scoping to names, but does not cover pagination, rate limits, or auth requirements. The description adds some value but lacks essential behavioral context beyond what is implicit.
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?
Three sentences, each serving a purpose: defining scope, noting performance, and providing usage alternatives. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, and 4 parameters with 0% schema description coverage, the description is too sparse. It omits details about pagination, optional filters, return format, and error cases, leaving the agent underinformed for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only implicitly refers to campaign_id and query via 'by NAME within a campaign'. Parameters 'types' and 'page' are not mentioned at all, nor their purposes or constraints. The description fails to add meaning beyond the raw schema.
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 clearly states the tool searches entities by name within a campaign, distinguishing it from full-text search and listing tools. It specifies 'matches names only (no entry/body text)', which is precise.
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?
Explicit guidance is provided: 'Prefer this when you know the entity name' and alternatives are named (kanka_full_text_search for body text, kanka_list_entities for browsing). This directly helps the agent decide when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It indicates the operation is permanent and requires confirmation, and it warns about caching effects. This is clear behavioral information, though it does not discuss reversibility or side effects on related data.
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?
The description is extremely concise: two sentences that front-load the purpose and key requirement. Every sentence adds value, with no wasted words. It is perfectly sized for a straightforward tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the primary behavior and a caching caveat, but given the lack of output schema and annotations, it does not explain the return value or error scenarios. For a delete tool, knowing what to expect in response would enhance completeness. Without that, it is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It only explains the `confirm` parameter (must be true) and hints at `entity_id` for cache busting. The other parameters (`campaign_id`, `entity_type`, `id`) are not described, leaving significant gaps for a tool with 5 parameters.
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 clearly states the tool deletes an entity permanently. It uses the specific verb 'delete' and resource 'entity', and the title 'Delete entity' reinforces this. It is distinct from siblings like kanka_create_entity, kanka_update_entity, and kanka_get_entity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly requires `confirm: true` to execute, providing a key usage condition. It also gives a note about cache behavior for `entity_id`. However, it does not explicitly state when to use this tool versus alternatives, though the purpose implies its use for deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility. It discloses that the tool paginates, strips HTML, matches locally, and returns snippets. It also mentions API budget consumption. It does not detail performance implications or potential failure modes, but covers the key behaviors.
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?
The description is two sentences, front-loading the purpose and mechanism, then cost advice. No wasted words, each sentence adds value. Ideal length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the core search mechanism and cost, but omits details on parameter usage for 6 of 8 parameters. No output schema, so return format is barely mentioned ('snippet'). More guidance on parameter semantics would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only adds guidance for 'types' and 'max_pages_per_type'. Other parameters like 'query', 'campaign_id', 'per_page', 'limit', 'case_sensitive', and 'regex' are left unexplained. The description adds limited value beyond the schema.
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 specifies the action 'search' and the resource 'body text of entities', and explains the method (paginating, stripping HTML, matching locally). It distinguishes from sibling tools like kanka_search, which likely does a different kind of search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit guidance: 'Costs API budget — narrow types and lower max_pages_per_type to keep it cheap.' It warns about cost and suggests parameter tuning. It does not explicitly state when not to use, but the cost implication implies alternatives might be preferred for small searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 explains the key trait that relations use global entity_ids and the two_way option. However, it does not disclose side effects of delete/update, authentication requirements, or pagination behavior. For a CRUD tool with 7 parameters, more behavioral context 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with four short sentences, each adding necessary information. There is no redundancy or filler. It efficiently conveys the tool's purpose, key concepts, and an optional feature.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, nested data object, no output schema, no annotations), the description provides essential information but leaves gaps. It does not explain the structure of data beyond target_id and two_way, pagination with page, or error scenarios. More complete context would help an agent invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 14%, so the description must compensate. It adds meaning for entity_id (global entity_id), and explains that data contains target_id and two_way. This significantly clarifies the data object. However, confirm and page parameters remain unexplained.
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 clearly states the CRUD operations on 'relations between entities', specifying the resource and actions. It distinguishes from sibling tools that deal with entities themselves, and adds detail about the use of global entity_id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that relations are based on the source's global entity_id and that target_id in data is the destination's global entity_id. It also mentions the two_way option for reciprocal relations. However, it does not explicitly state when to use this tool versus alternatives, though no direct alternative exists among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description fully bears the transparency burden. It discloses side effects (opens browser, persists tokens to disk) and prerequisites (OAuth app registration, env var fallback). This is adequate for a login tool.
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?
The description is four concise sentences, each contributing essential information: purpose, flow, persistence, and prerequisites. No redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of OAuth flows and absence of output schema/annotations, the description covers purpose, flow, persistence, and prerequisites. It lacks details on error handling or redirect URIs, but is sufficient for a login tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds meaning by explaining that client_id and client_secret can be provided directly or via environment variables. However, it does not specify formats, constraints, or defaults, so value is moderate.
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 clearly identifies the tool as running the OAuth 2.0 Authorization Code flow with PKCE, specifying the action (run, opens, persists) and resource (Kanka authorize page, tokens). It distinguishes from siblings like kanka_auth_logout and kanka_auth_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use this tool (to authenticate for subsequent calls) and prerequisite requirements (registered OAuth app, env vars). It does not explicitly state when not to use it or list alternative tools, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavioral traits. It mentions the delete action requires confirm: true, implying destructiveness, but does not elaborate on other side effects (e.g., irreversible changes, permissions). The global entity_id detail is helpful, but more context on mutation behaviors would improve transparency.
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?
Two concise sentences: the first states purpose, the second provides usage guidance. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 params, nested objects, no output schema), the description covers actions, required fields, and the global entity_id nuance. It omits return value details and pagination behavior for list, but the action-field mappings are adequate for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (14%), so the description compensates by explaining the action parameter and mapping each action to required fields (e.g., create needs data). It also reinforces the global entity_id usage. This adds significant meaning beyond the bare schema.
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 clearly states the tool performs CRUD operations on posts (sub-notes) attached to an entity, specifying the verb and resource. It distinguishes from sibling entity tools by focusing on posts and the global entity_id concept.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists the actions and required fields for each operation (e.g., list requires page, delete requires id and confirm), providing clear usage guidance. It does not explicitly state when not to use or compare to siblings, but the specificity is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only nature and 60-second caching, which are key behavioral traits. However, without annotations, it does not mention authentication requirements (though 'authenticated user' is stated) or pagination behavior beyond the schema.
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?
Two sentences efficiently cover purpose, usage, and caching. No extraneous text; front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one optional parameter and no output schema, the description covers purpose, usage context, and caching. The missing documentation of the 'page' parameter is a minor gap given its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain the 'page' parameter at all, despite 0% schema description coverage. The agent receives no guidance on how pagination works or how to use this optional parameter.
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 clearly states the tool discovers accessible Kanka campaigns and provides the campaign_id for subsequent operations, distinguishing it from siblings like kanka_get_campaign and kanka_list_entities.
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?
Explicitly advises calling this first to obtain campaign_id for entity-level operations and notes caching behavior (60 seconds) with a hint to recall if campaigns may have changed, providing clear when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 clearly states what is cleared (OAuth tokens) and what is not (API token), which is sufficient for a logout operation.
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?
Two concise sentences, front-loaded with the key action, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple logout action with no output schema, the description provides enough context. It could mention the expected response, but it's not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description adds no parameter-specific info, but the baseline for 0 parameters is 4, and the description does not need to compensate.
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 clearly states the verb 'Clear' and the resource 'stored OAuth tokens (access + refresh)'. It is specific and distinguishes from sibling tools like kanka_oauth_login.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clarifies that personal API tokens are unaffected, providing context. However, it does not explicitly state when to use this tool over alternatives, though it is implicit for logout scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses it is a PATCH (partial update) and clarifies id semantics. No annotations provided, so description carries full burden. Lacks details on permissions or error states but sufficient for a simple update.
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?
Two sentences, no fluff. Front-loaded with action and purpose. Efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description covers essential aspects: partial update, field selection, id type. Could mention response format, but not critical for a well-known operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, description adds value for 'id' (type-scoped) and 'data' (partial update). Does not describe campaign_id or entity_type, but enum for entity_type is in schema. Compensates partially.
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?
Clearly states 'Partial update (PATCH) on an existing entity'. Verb 'update' and resource 'entity' are specific. Distinguishes from sibling tools like create_entity and delete_entity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit instruction: 'Provide only the fields you want to change.' Clarifies id is type-scoped, not entity_id. However, no explicit when-not-to-use or alternative mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It discloses return format including two IDs and hints at dynamic schema for `data`. Lacks explicit authorization or error behavior, but sufficient for a creation tool.
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?
Two sentences, front-loaded with core purpose, no redundant words. Every sentence serves a purpose.
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?
Given the complexity (nested object, many entity types, no output schema), the description provides a complete workflow: create, prerequisite, and return info. Directing to describe_entity_type fills the gap for data schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains `data` is type-dependent and directs to describe_entity_type, but does not describe `campaign_id` or `entity_type` beyond schema enum. Adds moderate value.
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?
Clearly states 'Create a new entity', a specific verb and resource. Distinguishes from siblings like update/delete/list. Provides prerequisite hint and return value description.
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?
Explicitly instructs to call kanka_describe_entity_type first to discover the per-type schema for `data`, which is a crucial usage guideline for correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 states the tool returns a JSON Schema, which is a read-only behavior. It does not mention side effects, authentication, or rate limits, but for a simple schema retrieval, this is sufficient and transparent.
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?
The description consists of two concise sentences. The first sentence states the core purpose, and the second provides usage guidance. Every word earns its place with no redundancy.
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 tool is simple (one parameter, no output schema). The description fully explains its purpose and relationship to sibling tools, making it complete for an AI agent to understand when and why to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, 'entity_type', has an enum in the schema. The description does not explicitly describe the parameter, but it adds meaning by linking it to the purpose of retrieving the schema for that entity type. Given the enum is self-explanatory and the description provides context, it adds sufficient semantic value beyond the schema.
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 clearly states the tool returns a JSON Schema for the create/update payload of a Kanka entity type. It explicitly names the target resources (kanka_create_entity, kanka_update_entity) and their relationship, distinguishing from sibling tools by specifying it should be called before them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('before kanka_create_entity or kanka_update_entity to discover required and optional fields'). It implies when not to use it (after creating/updating, or for other operations not needing schema discovery). It provides clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must convey behavior. It accurately implies read-only operation via 'browse' and 'list', and reveals the incremental sync mechanism. It does not explicitly mention authentication needs or rate limits, but these are common and not required for scoring high transparency.
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?
Two concise paragraphs with front-loaded purpose and sibling alternatives, followed by a dedicated explanation of incremental sync. No redundant sentences; every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers browsing, filtering, and sync, but lacks details on the response structure (e.g., entity object format, pagination metadata) since there is no output schema. This is a gap for a tool with nested parameters and sync tokens.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is low (17%), but the description adds meaning by specifying filtering by type/name/tags and explaining the 'since' parameter for incremental sync. It does not elaborate on basic pagination parameters (page, per_page), but those are self-explanatory.
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 clearly states the tool browses campaign entities with enumeration, paging, and filtering by type/name/tags. It distinguishes itself from siblings by directing users to kanka_get_entity for specific IDs and kanka_full_text_search for text search, making the purpose unambiguous.
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?
Explicitly instructs when to use this tool versus alternatives (kanka_get_entity for ID lookup, kanka_full_text_search for text search). Also provides clear guidance on incremental sync usage with 'since' parameter and 'sync' token.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It clearly describes a read-only check of credential status without side effects. However, it doesn't explicitly state that it does not modify any state, which would be helpful but is not critical given the context.
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?
Two sentences, highly concise, with the key purpose and usage guidance front-loaded. No wasted words.
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?
No output schema exists, but the description explains what the tool returns (credential source and availability). This is sufficient for a simple status check tool, and all necessary context is provided.
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?
The tool has zero parameters, so no parameter documentation is needed. Baseline for 0 parameters is 4, but the description is perfect for this case.
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 clearly states the tool checks for a usable Kanka credential and identifies its source (env var, token file, OAuth, or none). This specific verb+resource distinguishes it from sibling tools like kanka_auth_logout or kanka_oauth_login.
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?
Explicit guidance: 'Call this first if other tools return AUTH_REQUIRED — it'll tell you what's missing.' This tells the agent when to use it and implies it's a diagnostic step before other auth-dependent tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![kanka-mcp MCP server](https://glama.ai/mcp/servers/torinvdb/kanka-mcp/badges/card.svg)](https://glama.ai/mcp/servers/torinvdb/kanka-mcp)

Score Badge

Copy to your README.md:

[![kanka-mcp MCP server](https://glama.ai/mcp/servers/torinvdb/kanka-mcp/badges/score.svg)](https://glama.ai/mcp/servers/torinvdb/kanka-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/torinvdb/kanka-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server