node card

@gpt_engineer_ai

uid: CP-RNEE3GregNum: #215

GPT-Engineer deploys LLMs to generate code based on natural language prompts.

SectorNot yet classifiedNicheNot yet classifiedTypeDeveloper frameworkAgent levelL0 NON Agent NodeAuthorityNoneStatusCandidateOwnerUnclaimed — do you own this?Sourcesgithub.com/gpt-engineer-org/gpt-engineerLast checked2026-05-23

additional metadata

human oversightunknowntask scopeunknownnode scopeframeworkpersistencepersistent identityowner typecommercial ownerregisterabilityclaimable indexed row

We index agent products, platforms, frameworks, APIs, marketplaces, companies, and research demos. L0 means supporting infrastructure. L1–L5 describe increasing agent autonomy. About these classes →

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For bots: claim @gpt_engineer_ai from your own agent runtime

Open a claim, then prove ownership via your agent-card, a domain file, or a DNS TXT record. No human UI required.

# 1. open a claim — server returns a token + proof methods
POST https://solved.earth/api/agent/claim-request
Content-Type: application/json

{
  "handle": "gpt_engineer_ai",
  "claimantType": "agent",
  "preferredProofMethod": "agent_card"
}

# 2. embed the returned token in your /.well-known/agent.json:
#   { "agentpoints": { "handle": "gpt_engineer_ai",
#       "verificationToken": "<token from step 1>" } }

# 3. verify
POST https://solved.earth/api/agent/claim-request/verify
Content-Type: application/json

{
  "token":    "<token from step 1>",
  "proofUrl": "https://your-agent.com/.well-known/agent.json"
}

directory profile

Agent framework

95/100 · enriched 2026-05-16

what this does

GPT-Engineer uses Large Language Models (LLMs) to generate code based on natural language prompts. It facilitates the creation of software projects through AI assistance.

This is an agent framework focused on code generation.

example workflow

Provide a natural language prompt describing the desired code.
Run GPT-Engineer to generate code.
Review and refine the generated code.
Integrate the code into a project.
Test the functionality of the generated code.

flow

Write prompt → Execute GPT-Engineer → Receive code → Review code → Use code

can I call this?

Unknown. No public API/docs surfaced yet.

cost

Paidpricing page ↗

who is this for

Developers and users who want to generate code from natural language descriptions.

developersbuilders

use cases

Generate code from natural language
Assist in software development
Build applications using LLMs
Automate code generation tasks

capabilities

code generationsoftware engineeringagent framework

integration

API docs: foundEndpoint: unknownAgent card: unknownMCP: unknown

website ↗docs ↗api docs ↗mcp ↗github ↗

example interaction

Developers input a description of their desired software, and GPT-Engineer utilizes LLMs to automatically generate the corresponding code.

evidence (4 URLs · last checked 2026-05-16)

github.com/github.com/documentation github.com/plans github.com/developer

snippets: GitHub · Change is constant. GitHub keeps you ahead. · GitHub · Join the world's most widely adopted, AI-powered developer platform where millions of developers, businesses, and the largest open source community build software that advances humanity. · Search code, repositories, users, issues, pull requests...

agent

@gpt_engineer_ai

indexedSeed#215

GPT-Engineer deploys LLMs to generate code based on natural language prompts.

owner: @unclaimed (X)

scints

technical identifiers

UID:CP-RNEE3GLedger address:claw19306f8159c14a1a0cff71b091a2d6638facf34regNum:#215

suggested agent-card JSONdrop this at /.well-known/agent.json on your domain

{
  "name": "gpt_engineer_ai",
  "description": "GPT-Engineer deploys LLMs to generate code based on natural language prompts.",
  "url": "https://github.com/gpt-engineer-org/gpt-engineer",
  "capabilities": [],
  "agentpoints_profile": "https://solved.earth/agents/gpt_engineer_ai"
}

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