A
licenseNot graded
qualityC
maintenanceEnables auditing and drafting of AI agent files (CLAUDE.md, AGENTS.md, Cursor rules) and turning project descriptions into full build specs, with local and API-based tools.
36 npm
MIT
raptr-agent-builder
Server Details
Turn an idea or meeting transcript into a working single-file AI agent, check it, use it right away.
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- Status
- Healthy
- Uptime
- 100.0% over the last 24 hours
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-06-18
- URL
- Repository
- airaptr/airaptr.github.io
- GitHub Stars
- 0
- ChatGPT
- –
- Claude
- –
TDQS
A4.1/5.0
Scored across 9 tools
Disambiguation4/5
The core agent lifecycle tools (get_agent_template, check_agent, use_agent_here) are clearly distinguished by descriptions, and discovery vs retrieval (find_agents vs get_agent_code) is well separated. The only mild overlap is use_agent_here versus how_to_run_agent (run in-chat vs run locally), but their descriptions clarify the distinction. rejection_rescue_preview is fully orthogonal to the agent-building purpose.
Naming Consistency4/5
Most tools follow a clean verb_noun pattern (check_agent, find_agents, get_agent_code, share_agent, use_agent_here). rejection_rescue_preview deviates from the pattern and omits 'agent', and how_to_run_agent uses a phrase-style name, but overall the set is readable and predictable.
Tool Count5/5
Nine tools is well-scoped for a server covering discovery, building, validating, running, and sharing agents. Each tool maps to a distinct stage of the workflow and none feels redundant.
Completeness4/5
The set covers the full agent lifecycle: find existing agents, fetch code, get a template, validate, run in-chat, run locally, and share/publish, plus a fallback request_service. The main oddity is rejection_rescue_preview, which is tangential to agent building and hints at a possible missing 'app review' domain rather than an agent-builder gap.
Available Tools
9 toolscheck_agentCheck an agent fileARead-onlyInspect
Checks a finished agent file against the template rules (manifest, naming, class, perform method, no hardcoded secrets). Call it on every agent you write, fix anything it reports, and call it again until it passes.
Inputs: code (required), filename (required).
find_agentsFind existing agentsARead-onlyInspect
Searches the open agent registry (about 1,700 single-file agents) for agents that already do what the user wants, for example when they ask 'is there an AI tool for...' or want a ready-made automation instead of building one. Use it before building from scratch, or when the user asks whether an agent exists for a task.
Inputs: query (required), limit.
get_agent_codeGet an agent's codeARead-onlyInspect
Returns the full source of one agent from the registry, by its name (e.g. @bill/neuron_agent), so it can be read or adapted.
Inputs: name (required).
get_agent_templateGet the agent templateARead-onlyInspect
Use this when the user wants to build an AI agent, assistant, bot or automation from an idea, a repetitive task, a process description, or a meeting transcript (for example: automate invoices, triage support tickets, summarize meetings, follow up with leads). Returns the official single-file agent template and its rules. Fill it in yourself from what the user described, then call check_agent on the finished file before showing it to the user. Then call use_agent_here so the user can use it right away in this chat.
Inputs: no named parameters.
how_to_run_agentKeep an agent running on your computerARead-onlyInspect
Optional, for later: how to keep an agent running on the user's own computer with the free Brainstem. Only offer this after the user has used the agent in the chat and wants to keep it.
Inputs: os, filename.
rejection_rescue_previewExplain an App Store rejectionARead-onlyInspect
Use when the user pastes a rejection message from Apple App Review (it cites guidelines such as "Guideline 5.1.1(i)"). Free. Returns each cited guideline section it recognizes, with its title and what Apple means by it, and lists sections it does not know. The full version (likely causes, a fix list and a reply draft to App Review) is a separate paid HTTP call; the result says its price and route.
Inputs: text (required).
request_serviceAsk us to build somethingAInspect
Use when the person wants something none of these tools can do and says yes to passing the request on. Records only the request text they agree to send (no name or contact). Ask before calling it.
Inputs: request (required).
use_agent_hereUse the agent in this chatARead-onlyInspect
Use this right after an agent passes check_agent, or whenever the user wants to try an agent. Returns a short Python runner so you can run the agent in this chat with your own Python tool on the user's own data (pasted text, an uploaded spreadsheet, a list). Nothing to install. If Python is unavailable, apply the agent's logic yourself by reading its code. Ask the user for their real data, run the agent, and show the result in plain words.
Inputs: filename.
Tool Schema Changelog
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