The AgentBase MCP Server gives AI agents programmatic access to search and retrieve agent instruction files from the AgentBase open registry. Here's what you can do:
Search the registry (search_registry): Find instruction files — system prompts, skills, workflows, domain packs, safety filters, and orchestration patterns — by keyword, category, minimum quality score, or featured status.
Retrieve a specific instruction file (get_instruction): Fetch a file by its slug, including YAML frontmatter, purpose, usage notes, and deployable instruction text, with an option to return only the raw deployable instruction.
List all categories (list_categories): Browse all available categories with descriptions and file counts.
Get featured files (get_featured): Retrieve curated, top-rated (quality score 90+), verified, and production-tested instruction files.
This enables AI agents to dynamically load domain-specific instructions at runtime, share and reuse prompts across teams, and implement tested safety filters and workflows — all from a centralized registry.
MCP server for the AgentBase agent instruction registry. Gives any MCP-compatible AI agent direct access to search and retrieve instruction files.
Listed in punkpeye/awesome-mcp-servers — 83k+ stars.
AgentBase is an open registry of agent instruction files: system prompts, skills, workflows, domain packs, safety filters, and orchestration patterns. This MCP server wraps the registry's HTTP endpoints and exposes them as structured MCP tools.
Related MCP server: Clawslist MCP Server
Tool | Description |
| Search instruction files by keyword, domain, or type |
| Retrieve a specific instruction file by ID |
| List all available categories and domains |
| Get featured/top-rated instruction files |
{
"mcpServers": {
"agentbase": {
"command": "npx",
"args": ["-y", "@agentbase1/mcp-server"]
}
}
}AI agents that need to load domain-specific instructions at runtime
Claude Code workflows that pull skills from a shared registry
Teams sharing system prompts and workflows across agents
Safety filter retrieval for production AI deployments
Browse the full registry at agentbase-registry.vercel.app.
CC0 licensed. All instruction files are free to use without restriction.
Chris Izworski — Solutions Consultant at Prepared, former Michigan 911 Executive Director, and AI implementer. Bay City, Michigan.
Website: chrisizworski.com
GitHub: github.com/izworskic
Wikidata: Q138283432
Return all featured instruction files (quality score 90+). These are verified, complete, and production-tested. Good starting point for finding high-quality instructions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 discloses behavioral traits: the tool returns files with specific quality criteria (90+), and they are verified/complete/production-tested. However, it lacks details on rate limits, authentication needs, or potential side effects, which are important for a tool with no 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?
The description is appropriately sized with two sentences that are front-loaded: the first states the core action and criteria, and the second adds context on quality and usage. Every sentence adds value without waste, making it efficient and well-structured.
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 has no parameters, no annotations, and no output schema, the description provides basic context (purpose, quality criteria, usage hint). However, for a tool that returns data, it lacks details on output format, pagination, or error handling, leaving gaps in completeness despite the low complexity.
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 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add param info, but with no params, the baseline is 4 as it doesn't need to compensate for gaps. It does imply the quality score threshold, which is a semantic constraint not in 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's purpose: 'Return all featured instruction files (quality score 90+)'. It specifies the resource (featured instruction files) and the selection criteria (quality score 90+). However, it doesn't explicitly differentiate from sibling tools like 'get_instruction' or 'search_registry', which might also retrieve instructions.
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 implies usage by stating these files are 'verified, complete, and production-tested' and a 'good starting point for finding high-quality instructions'. This suggests when to use it (for high-quality starting points), but it doesn't provide explicit alternatives or exclusions compared to sibling tools like 'search_registry' for filtered searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a complete instruction file from the OpenClaw registry by slug. Returns the full Markdown file including YAML frontmatter, purpose, usage notes, and the deployable instruction text. The instruction is in the "## The Instruction" section.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The slug of the instruction file (e.g. "tier1-customer-support", "structured-web-research"). Get slugs from search_registry. | |
| instruction_only | No | If true, return only the deployable instruction text (extracted from the fenced code block). If false, return the full Markdown file. Default: false. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the return format (full Markdown or extracted instruction text) and hints at the structure (YAML frontmatter, sections), but lacks details on error handling, rate limits, or authentication needs. It adds some behavioral context but is not comprehensive.
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 front-loaded with the core purpose, followed by details on return content and parameter implications. Every sentence adds value without redundancy, making it efficient and well-structured for quick understanding.
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 (2 parameters, no output schema, no annotations), the description is mostly complete. It covers purpose, usage context, and return behavior, but lacks explicit error handling or output examples, which could enhance completeness for an agent.
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 100% description coverage, so the baseline is 3. The description adds minimal value beyond the schema by mentioning the '## The Instruction' section, which relates to the 'instruction_only' parameter, but does not provide additional syntax or format details. It compensates slightly but not significantly.
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 specific action ('Fetch'), resource ('complete instruction file from the OpenClaw registry'), and distinguishes it from siblings by specifying it retrieves by slug rather than listing categories or searching. It explicitly mentions the return content format, 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by stating that slugs should be obtained from 'search_registry', which implicitly guides when to use this tool versus alternatives. However, it does not explicitly state when not to use it or name specific alternatives, keeping it from a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all categories in the OpenClaw registry with file counts and descriptions. Use this to understand what types of instruction files are available.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool lists categories with file counts and descriptions, but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, or how results are structured (e.g., pagination). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 two sentences, front-loaded with the core purpose and followed by a usage hint. Every sentence adds value without redundancy, making it efficient and well-structured 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 tool's low complexity (0 parameters, no output schema, no annotations), the description is adequate for basic understanding but incomplete. It covers what the tool does and a usage context, but lacks behavioral details (e.g., safety, performance) that would be important even for simple tools, especially without annotations to fill those gaps.
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 0 parameters, and the schema description coverage is 100% (since there are no parameters to describe). The description appropriately doesn't add parameter details beyond what the schema provides, which is minimal. A baseline of 4 is applied for zero-parameter tools as they inherently require less parameter documentation.
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 ('List all categories') and resource ('OpenClaw registry'), specifying what information is returned ('file counts and descriptions'). It distinguishes from siblings by focusing on categories rather than individual instructions or searches, though it doesn't explicitly contrast with sibling tools like get_featured.
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 provides implied usage context ('to understand what types of instruction files are available'), suggesting this tool is for discovery and overview. However, it lacks explicit guidance on when to use this versus alternatives like search_registry or get_instruction, and doesn't mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the OpenClaw agent instruction registry. Returns matching instruction files with metadata. Use this to find system prompts, skills, workflows, domain packs, safety filters, and orchestration patterns.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Keyword search across title, tags, and slug. Optional. | |
| category | No | Filter by category. One of: system-prompts, skills, workflows, tool-definitions, domain-packs, safety-filters, orchestration | |
| min_quality | No | Minimum quality score (0-100). Recommended: 80 for production use. | |
| featured_only | No | If true, return only featured (quality >= 90) files. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns 'matching instruction files with metadata,' which implies a read-only search operation, but does not disclose other behavioral traits such as authentication requirements, rate limits, pagination, error handling, or what the metadata includes. This leaves significant gaps in understanding how the tool behaves beyond its 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 two sentences that are front-loaded with the core purpose and usage context, with zero wasted words. Every phrase ('Search the OpenClaw agent instruction registry,' 'Returns matching instruction files with metadata,' 'Use this to find...') directly contributes to clarity and guidance, making it highly efficient and well-structured.
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 (4 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and usage context well, but lacks details on behavioral aspects (e.g., response format, error cases) and doesn't compensate for the missing output schema. This makes it minimally viable but with clear gaps in providing a full operational picture.
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 schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description does not add any parameter-specific details beyond what the schema provides (e.g., it doesn't explain search syntax for 'q' or elaborate on 'min_quality' beyond the schema's 'Recommended: 80'). Thus, it meets the baseline for high schema coverage but doesn't enhance parameter understanding.
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 specific action ('Search') and resource ('OpenClaw agent instruction registry'), and distinguishes it from siblings by specifying it returns 'matching instruction files with metadata' rather than getting featured items, single instructions, or listing categories. It provides concrete examples of what can be found (system prompts, skills, workflows, etc.), making the purpose highly specific and differentiated.
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 provides clear context for when to use this tool ('to find system prompts, skills, workflows, domain packs, safety filters, and orchestration patterns'), which implicitly suggests alternatives like the sibling tools for other purposes (e.g., get_featured for featured items). However, it does not explicitly state when NOT to use this tool or name specific alternatives, which prevents a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.2get_featuredget_instructionlist_categoriessearch_registryEach tool has a clearly distinct purpose with no overlap: get_featured retrieves high-quality files, get_instruction fetches a specific file by slug, list_categories shows available categories, and search_registry performs keyword searches. The descriptions reinforce these unique roles, making tool selection straightforward for an agent.
All tool names follow a consistent verb_noun pattern (get_featured, get_instruction, list_categories, search_registry) using snake_case throughout. This predictability enhances readability and usability, with no deviations in style or convention.
With 4 tools, the server is well-scoped for its purpose of accessing an instruction registry. Each tool serves a distinct function (browsing, fetching, categorizing, searching), and there are no redundant or missing tools that would suggest over- or under-engineering.
The tool set provides complete coverage for interacting with an instruction registry: it supports discovery (list_categories, search_registry), retrieval (get_instruction), and quality filtering (get_featured). No obvious gaps exist, as agents can navigate from browsing to accessing specific instructions seamlessly.
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