Fully Autonomous AI Agent — No API Credits Required
The 
gent
Eight parallel workers. Zero cloud dependencies. Runs on your machine forever.
The autonomous agent that thinks, acts, and evolves — without asking permission.
8×Parallel Tasks
$0API Cost
∞Runtime
100%Local Execution
Autonomous Agent Loop ·8 Parallel Workers ·Zero API Credits ·Local LLM Inference ·Pump.fun Agentic Mode ·Buyback & Burn ·On-Chain Tokenomics ·Memory Persistence ·10+ Built-in Tools ·Self-Healing Tasks ·Autonomous Agent Loop ·8 Parallel Workers ·Zero API Credits ·Local LLM Inference ·
Autonomous Agent Loop ·8 Parallel Workers ·Zero API Credits ·Local LLM Inference ·Pump.fun Agentic Mode ·Buyback & Burn ·On-Chain Tokenomics ·Memory Persistence ·10+ Built-in Tools ·Self-Healing Tasks ·Autonomous Agent Loop ·8 Parallel Workers ·Zero API Credits ·Local LLM Inference ·
Capabilities
Built differently.
Runs differently.
Octogent is not a wrapper around a cloud API. It is a fully autonomous execution engine that lives on your hardware — persistent, private, and uncapped.
01
8-Slot Worker Pool
Execute up to eight independent tasks simultaneously using Node.js worker_threads. Each slot runs its own agent loop — completely isolated.
↗02
Zero API Costs
Runs fully on Ollama local models. No tokens, no billing, no rate limits. Groq cloud fallback available for burst workloads.
↗03
Autonomous Loop
Think → Act → Observe. The agent plans its own steps, selects tools, executes them, evaluates results, and retries failures — unsupervised.
↗04
Persistent Memory
SQLite-backed long-term memory across all sessions. The agent remembers what it has done, learned, and built.
↗05
10+ Native Tools
bash, read_file, write_file, web_search, web_fetch, memory, spawn_agent, check_task, and more. All sandboxed.
↗06
Skills System
Define agent personas in JSON — Coder, Researcher, Writer, DevOps. Each skill shapes how the agent thinks and which tools it favors.
↗Architecture
How the agent thinks.
Every task passes through a deterministic loop. No randomness, no magic — just a structured system that reasons, acts, and self-corrects.
01
Task Intake
A task arrives via CLI, WebSocket, or cron. It is validated, queued, and assigned to the next available worker slot in the pool.
ws://127.0.0.1:1878902
Planning
The agent uses the LLM to decompose the task into atomic steps. It selects the appropriate skill profile and loads relevant memory context.
Think phase03
Execution
Each step is executed via the tool layer — bash, file ops, web fetch, sub-agent spawn. Tool outputs are captured and passed back to the model.
Act phase04
Observation
The model evaluates tool results. If a step fails, it retries with a revised approach up to the configured maxIterations limit.
Observe phase05
Memory Write
On completion, key findings are written to SQLite long-term memory. The agent's knowledge compounds with every task.
Persist$OCTOGENT
Autonomous tokenomics.
No team. No hands.
The token runs on Pump.fun Agentic Mode — a fully programmatic buyback and burn mechanism. 100% of all trading fees are routed directly to the agent. It buys. It burns. It never stops.
Autonomous Buybacks
The agent monitors market conditions 24/7 and executes strategic buybacks using accumulated trading fees. Pure algorithmic execution. Zero team involvement.
Perpetual Burns
Every purchased token is sent to the burn address automatically. Supply decreases with every transaction. Deflationary mechanics baked into the protocol.
100% Fee Allocation
Every fee generated flows directly to the agent's execution wallet. No team cut. No marketing allocation. Value returned to holders only.
Pump.fun Agentic Mode
Built on Pump.fun's Agentic Mode — the first programmatic market operation layer for on-chain tokens. The agent acts as the sole market participant.
100%Fees to Agent
0%Team Allocation
24/7Autonomous Ops
Installation
Deploy in minutes.
Octogent runs on Node.js 18+ with Ollama for local model inference. No cloud accounts. No API keys. Just your machine.
Runtime
Node.js >= 18.0
Model Backend
Ollama (local)
RAM Minimum
8 GB
Storage
20 GB (models)
OS
macOS / Linux / WSL2
Optional
GPU (CUDA / Metal)
octogent — terminal
Step 1 — Install Ollama
$curl -fsSL https://ollama.com/install.sh | sh
$ollama pull llama3.2:8b-instruct-q8_0# ~5 GB
Step 2 — Initialize Octogent
$npx octogent@latest init
$octogent config --model llama3.2:8b --threads 8
Step 3 — Launch & Run
$octogent start# starts daemon
$octogent task "Build a REST API for user management"
$octogent workers# monitor all slots
Supported models:
Groq cloud fallback requires
llama3.2:8b · llama3.1:70b · qwen2.5-coder:14b · deepseek-r1:14b · mistral:7bGroq cloud fallback requires
GROQ_API_KEY in your environment.Explore
Go deeper.
Deep DiveAgent ArchitectureHow the autonomous loop works. Tool selection, memory, sub-agent spawning, and the full execution model.↗TechnicalModel ParametersSupported LLMs, inference parameters, quantization options, context windows, and performance benchmarks.↗ReferenceDocumentationFull CLI reference, configuration schema, environment variables, and integration guides.↗