ikhono
Server Details
The HUB of ai skills Publish, discover, and use AI agent skills across all platforms. Connect the MCP server once and every skill on the registry becomes instantly available — no local installation needed.
- 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 6 of 6 tools scored.
Each tool has a clearly distinct purpose with no functional overlap. Search discovers skills, get retrieves specific content, pin/unpin manage favorites binary state, list_pinned displays favorites, and rate provides feedback. Descriptions clearly differentiate search (returns list with metadata) from get (returns full content).
All six tools follow the identical pattern 'ikhono_skill_[verb]' using consistent snake_case. The prefix identifies the domain, and verbs (get, search, pin, unpin, list_pinned, rate) are action-oriented and uniformly formatted.
Six tools is an ideal count for this skill marketplace domain. The set covers the complete user workflow—discovery (search), retrieval (get), curation (pin/unpin/list_pinned), and feedback (rate)—without bloat or missing essential operations.
Covers the core lifecycle for skill consumption: discovery, loading, favoriting, and rating. Minor gaps exist (no way to browse categories or view one's own rating history), but agents can successfully complete primary skill-based workflows. Missing administrative operations (create/update skills) are appropriately out of scope.
Available Tools
6 toolsikhono_skill_getAInspect
Load a skill from iKhono by its slug. Returns the full skill content (instructions, process, templates) that you should follow to complete the user's task. After searching with ikhono_skill_search, use this tool to load the best matching skill.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The skill slug (e.g., "@alice/security-reviewer"). Get this from ikhono_skill_search results. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses return value (full skill content with instructions/templates) compensating for lack of output schema, but omits idempotency/safety characteristics.
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, both high-value: first covers action/return, second covers workflow trigger; 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?
Comprehensive for a single-parameter tool; compensates for missing output schema by detailing return structure, though silent on error cases.
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 has 100% description coverage (slug fully defined), meeting baseline; description adds minimal semantic context beyond 'by its slug'.
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?
Clearly states it loads a skill by slug and returns full content; distinguishes from search sibling by prescribing the search-then-get workflow.
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 states when to use ('After searching with ikhono_skill_search, use this tool to load the best matching skill'), establishing clear workflow sequencing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ikhono_skill_list_pinnedAInspect
List all skills the user has pinned. Returns pinned skills with their names, descriptions, and ratings.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses return values (names, descriptions, ratings) since no annotations exist, but omits side effects, errors, or rate limits.
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 concise sentences: first states purpose, second explains return value; no filler content.
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?
Adequately covers return structure given no output schema exists and operation is simple, though edge cases not mentioned.
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?
Baseline score for zero parameters; no parameter explanation 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?
Specific verb 'List' with clear resource 'pinned skills', clearly distinguished from siblings like 'search', 'pin', and 'get'.
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?
Usage is implied by clear purpose statement, but no explicit when/when-not guidance or comparison to alternatives provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ikhono_skill_pinAInspect
Pin a skill to the user's favorites so it's always available. Pinned skills are shown in the user's profile.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The skill slug to pin (e.g., "@alice/security-reviewer") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description adequately covers behavioral traits by mentioning persistence ('always available') and visibility ('shown in profile'), though misses edge cases.
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 tightly written sentences—first establishes action/purpose, second clarifies effect/location—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?
Complete for this low-complexity tool (single param, no output schema); explains the 'what' and 'where' sufficiently.
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 100%, meeting baseline expectation; description adds no parameter-specific semantics but doesn't need to.
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?
Clear verb 'Pin' with resource 'skill', and 'favorites'/'profile' implicitly distinguishes from sibling tools like unpin/search/rate.
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?
Provides implied usage context ('always available') but lacks explicit when/when-not guidance or alternative comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ikhono_skill_rateBInspect
Rate a skill after using it. Helps the community discover the best skills.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The skill slug to rate (e.g., "@alice/security-reviewer") | |
| stars | Yes | Rating from 1 to 5 stars | |
| review | No | Optional text review |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, fails to disclose side effects (creating persistent rating), idempotency constraints, or return values.
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 front-loaded sentences with zero redundancy; 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?
Adequate for simple action but omits behavioral context (idempotency, return status) that would help invocation decisions.
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 has 100% coverage so baseline is met; description adds no parameter context but doesn't need to.
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?
Clearly states the action (rate a skill) and beneficiary (community discovery), implicitly distinguishing from sibling retrieval/management tools.
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?
Provides implied timing guidance ('after using it') but lacks explicit when-not-to-use rules or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ikhono_skill_searchAInspect
Search iKhono for AI skills that match a query. Use this when the user asks you to do something that could benefit from specialized expertise. Returns a list of matching skills with their names, descriptions, ratings, usage counts, and pin counts.
| Name | Required | Description | Default |
|---|---|---|---|
| mine | No | Set to true to show only your own skills (requires authentication) | |
| limit | No | Maximum number of results to return | |
| query | No | Search query to find relevant skills (e.g., "security review", "write tests", "api docs"). Leave empty when using mine or author filters to list all matching skills. | |
| author | No | Filter by author username (e.g., "@alice" or "alice") | |
| category | No | Filter by category (e.g., "security", "testing", "documentation") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses return values thoroughly (names, ratings, pins, etc.) compensating for missing output schema, but omits auth requirements for 'mine' parameter and rate limiting details.
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?
Three well-structured sentences: purpose, usage trigger, return values—each earning its place without 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?
Adequately compensates for missing output schema by detailing return structure; covers core functionality but could note all parameters are optional.
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 has 100% description coverage, meeting baseline; description adds no parameter-specific guidance beyond 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?
Clear specific action (search) and resource (AI skills), but lacks explicit differentiation from sibling tools like 'get' or 'list_pinned'.
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?
Provides explicit trigger ('when the user asks... specialized expertise'), but lacks guidance on when to use alternatives like skill_get for known IDs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ikhono_skill_unpinAInspect
Remove a skill from the user's pinned favorites.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The skill slug to unpin |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Explains the removal action but omits behavioral details like idempotency, error cases (skill not pinned), or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is perfectly sized, front-loaded, and efficient 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?
Adequate for simple one-parameter tool; covers intent sufficiently given no output schema exists to document.
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 has 100% coverage with 'The skill slug to unpin'; description meets baseline but adds no additional parameter context.
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?
Specific verb (Remove) + resource (skill from pinned favorites) clearly distinguishes from siblings like ikhono_skill_pin.
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?
Usage is implied by the name and sibling tools, but lacks explicit when-to-use vs alternatives guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$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
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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.
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