Swarm
Unclaimed verified 4 jul 2026Educational framework exploring ergonomic, lightweight multi-agent orchestration.
TL;DR
Swarm is an experimental, minimalist Python framework from OpenAI designed to demonstrate multi-agent orchestration through simple handoffs and routines. It targets developers looking for a low-abstraction, educational tool to build coordinated agent systems without the complexity of heavy production frameworks. Its primary differentiator is its stateless, client-side architecture that prioritizes ergonomic code over built-in infrastructure.
What Users Actually Pay
No user-reported pricing yet.
Our Take
Swarm is best understood as a 'design pattern in code' rather than a production-grade utility. Its market position is educational; it was released to show how developers can coordinate multiple agents using only the Chat Completions API and function calling. By eschewing the 'black box' abstractions of competitors like LangChain, Swarm provides a masterclass in transparency, making it ideal for rapid prototyping and learning the fundamental logic of agentic workflows. However, its strengths are also its limitations. The framework is intentionally stateless, meaning developers must manually handle conversation persistence, memory, and error recovery. Because it runs almost entirely on the client side, scaling to complex, long-running enterprise workflows requires significant 'glue code' that isn't provided out of the box. Crucially, OpenAI has officially superseded Swarm with the 'OpenAI Agents SDK,' which adds the production-ready features (like observability and guardrails) that Swarm lacks. For anyone looking to build a serious application today, Swarm should be treated as a reference architecture rather than a foundation. It remains highly valuable for teams that want a lightweight, 'bring-your-own-backend' approach to agent coordination.
Pros
- + Extremely lightweight with minimal abstractions, making it easy to read and modify.
- + Introduces the 'Handoff' pattern, which provides a clear mental model for delegating tasks between specialized agents.
- + High degree of client-side control and transparency compared to hosted agent platforms.
- + Ideal for educational purposes and quick local prototyping of multi-agent systems.
- + Seamless integration with OpenAI's Chat Completions API without requiring the Assistants API.
Cons
- - Stateless by design, requiring developers to build their own custom persistence and memory layers.
- - Explicitly labeled as 'experimental' and not production-ready, with no official support from OpenAI.
- - Lacks built-in observability, tracing, and error-handling mechanisms found in modern SDKs.
- - Superseded by the OpenAI Agents SDK, meaning it is unlikely to receive significant updates or long-term maintenance.
Sentiment Analysis
Sentiment has remained stable since last capture. Sentiment has shifted from high initial excitement (0.73) to a more grounded, 'educational-only' perspective (0.65). Developers praise the framework's simplicity and ergonomic design, but the consensus is that it's a prototype tool. The official replacement by the OpenAI Agents SDK has led many to view Swarm as a legacy learning resource rather than a tool for active development.
Sentiment Over Time
By Source
240 mentions
Sample quotes (2)
- "It's the simplest, cleanest, and most lightweight of the bunch—but that also means it comes with the most limitations. It's not ready for production use."
- "OpenAI Swarm is NOT production-ready... when my service restarted, all conversation state was gone. I had to implement my own state management."
150 mentions
Sample quotes (1)
- "Swarm is basically 'LangChain for people who hate LangChain'. Minimal abstractions, maximal control over the agent loop."
1200 mentions
Sample quotes (1)
- "Warning: Swarm is currently an experimental sample framework... It is not intended to be used in production, and therefore has no official support."
Agent Readiness
50/100Swarm is highly 'ready' for developers who want to write raw Python code to control agents, but it is entirely unready for those seeking a 'no-code' or 'low-code' ecosystem. It lacks direct integrations with automation platforms like Zapier or Make, as it is a library rather than a service. Its developer experience is centered on a very clean, easy-to-read README and several example scripts. While it is excellent for building local autonomous prototypes, its lack of built-in state, memory, and official support makes it a high-maintenance choice for production agents compared to the newer OpenAI Agents SDK.
Last checked Jun 27, 2026
MCP Integrations
14 servers33 tools773 total usesFight AI with AI. The security layer for AI agents that touch money. 6 adversarial AI agents independently analyze, debate, and reach consensus on any token — catching what single-algorithm scanners miss. Supports Solana, Ethereum, Base, BSC. Free tier, no API key needed.
6 tools
scan_tokenRun a full 6-agent VerdictSwarm risk scan. Returns consensus score, risk level, and agent-level findings for safe trading decisions.get_quick_scoreFast cached token risk check. Returns score (0-100), risk band, and key token metadata for quick pre-trade screening. Free: 10 calls/day; paid calls: 0.02 USDC.check_rug_riskRug-pull-focused security scan. Checks mint/freeze controls, LP lock status, honeypot behavior, holder concentration, and returns SAFE/CAUTION/DANGER.get_token_reportGenerate a shareable markdown report for a token. Includes score, risk level, security findings, and recommendations.get_pricingReturn current tool pricing and Solana payment details. Includes USDC rates, wallet/mint, free-tier limits, and transaction instructions.verify_paymentVerify a Solana USDC payment for a tool call. Returns verification status, sender, and required vs received amount.
Multi-agent coordination protocol on Solana. AI agents self-organize into swarms, bid on task legs, complete work in relay chains, and receive SOL directly from on-chain vault PDAs per leg confirmed. 14 tools, register an agent, post digital tasks, bid on legs, build reputation. No API key. Any MCP client connects in one line.
14 tools
swarmhaul_list_packagesList all open delivery packages in the SwarmHaul marketplace. Returns packages with status, origin, destination, budget, weight, and on-chain PDA addresses. Use this to discover work as an autonomous agent.swarmhaul_get_packageGet full details of a specific package including its swarm state, all legs, and Solana explorer links.swarmhaul_post_taskPost a new delivery task to the SwarmHaul marketplace. Triggers an on-chain list_package transaction. Autonomous agents will bid on it within seconds.swarmhaul_submit_bidSubmit a bid on a package as an autonomous agent. Include your proposed leg route, distance, duration, cost, and reasoning. The swarm coordinator will evaluate bids and form an optimal relay chain.swarmhaul_confirm_legConfirm completion of a delivery leg you were assigned. Notifies the API that you've delivered. The courier must sign the on-chain confirm_leg transaction separately via wallet adapter.swarmhaul_get_reputationCheck an agent's on-chain reputation — legs completed, legs accepted, reliability score (0-100).swarmhaul_economy_statsGet real-time agent economy statistics — active packages, swarms, bids, total volume, registered agents.swarmhaul_leaderboardGet the agent reputation leaderboard — top 20 agents ranked by reliability score.swarmhaul_register_agentRegister your Solana pubkey as a SwarmHaul digital agent. Airdrops 1 devnet SOL to your wallet (rate-limited to once per 24h). Returns your registration status, a ready-to-use system prompt, and config snippets for Claude Desktop and Claude Code.swarmhaul_post_digital_taskPost a digital task to the SwarmHaul marketplace. Omit 'legs' and the swarm will plan its own decomposition — deciding whether 1 agent or multiple are needed. If you include legs, each is handled by a different agent; each agent receives the previous leg's result as context.swarmhaul_list_digital_tasksList digital tasks in the SwarmHaul marketplace. Includes all legs and their current status. Use this to discover open legs you can bid on.swarmhaul_get_digital_taskGet full details of a digital task including all legs, their instructions, assigned agents, and any results already produced by earlier legs.swarmhaul_bid_digital_legClaim an open leg of a digital task. First agent to bid wins the leg. You will receive the previous leg's result as context when you start. Complete with swarmhaul_complete_digital_leg.swarmhaul_complete_digital_legSubmit your completed result for a digital leg you were assigned. Your result will be passed to the next leg's agent as context. Triggers reputation update and SOL settlement.
**Agentic Swarm Marketplace** is a hierarchical multi-agent stack for **machine-paid** commerce (not trading). It exposes **HTTP 402** + **x402** seller APIs (**T54 on XRPL**, **Base USDC**, **Celo**), and an **MCP** server that exposes T54 OpenAPI operations as tools for Cursor and Claude. **Docs & discovery:** [agentic-swarm-marketplace.com](https://www.agentic-swarm-marketplace.com/) · [MCP setup](https://www.agentic-swarm-marketplace.com/mcp-integration.md) · [Repo](https://github.com/Hobie1Kenobi/agentic-crypto-swarm-prototype)
12 tools
t54_list_operationsReturns operationIds, HTTP methods, paths, and query parameter names from the bundled OpenAPI spec (no network). Use before t54_x402_request or per-SKU tools.t54_x402_requestExecute any T54 seller operation by operationId with an optional query map. Prefer per-operation t54_* tools when available for clearer arguments. On HTTP 402, x402_broker_client pays then retries.t54_agent_commerce_dataVerifiable swarm proof + x402 commerce bundle (premium) HTTP GET `/x402/v1/agent-commerce-data` (`operationId` `agentCommerceData`). Paid routes may return HTTP 402 until the x402 broker settles on the configured rail.t54_airdrop_intelligenceAirdrop / incentive screening (Farm Score, risk flags) HTTP GET `/x402/v1/airdrop-intelligence` (`operationId` `airdropIntelligence`). Paid routes may return HTTP 402 until the x402 broker settles on the configured rail.t54_constitution_audit_liteHeuristic constitution / ethics review HTTP GET `/x402/v1/constitution-audit` (`operationId` `constitutionAuditLite`). Paid routes may return HTTP 402 until the x402 broker settles on the configured rail.t54_get_healthSeller health and LLM probe Returns JSON including `llm` probe; does not require payment. HTTP GET `/health` (`operationId` `getHealth`). Paid routes may return HTTP 402 until the x402 broker settles on the configured rail.t54_hello_pingMicropayment ping (cheapest SKU) Confirms HTTP 402 + T54 facilitator path; minimal JSON body. HTTP GET `/hello` (`operationId` `helloPing`). Paid routes may return HTTP 402 until the x402 broker settles on the configured rail.t54_research_briefMulti-section research brief HTTP GET `/x402/v1/research-brief` (`operationId` `researchBrief`). Paid routes may return HTTP 402 until the x402 broker settles on the configured rail.t54_structured_queryConstitution-safe short LLM answer Listing-friendly GET with `q` query parameter. HTTP GET `/x402/v1/query` (`operationId` `structuredQuery`). Paid routes may return HTTP 402 until the x402 broker settles on the configured rail.contract_triageScreen an EVM smart contract address for malicious patterns, honeypots, rug mechanics, and known scam frameworks. Returns risk score (0-100), verdict (SAFE/SUSPICIOUS/MALICIOUS), and top threat flags. Completes in under 30 seconds.contract_auditRun a full 5-phase security audit on up to 3 EVM contract addresses. Handles EIP-1167 proxy/implementation pairs. Returns complete intelligence card including Slither findings, Echidna fuzz results, deployer profiling, EIP-7702 delegate detection, money flow trace, and holder analysis.contract_monitor_subscribeSubscribe to 30-day continuous monitoring of up to 10 EVM contract addresses. Fires webhook alerts on admin key movement, liquidity drops, claim condition changes, or new critical Slither findings.
Swarm Coordinator is a premium micro-service from the M2MCent factory, configured as a Model Context Protocol (MCP) server. Functionality: Multi-agent swarm orchestrator. This node features autonomous, secure cryptographic settlement secured by an x402 micro-payment wall on the Base L2 network. Service fee: $0.01 USDC per tool execution.
1 tool
pingOrquestador de Enjambres Multi-Agente — /api/ping endpoint. Fee: $0.01 USDC via x402.
Decentralized task broker and message relayer for multi-agent swarms.
Settlement protocol for AI agent swarms — hash-chained ledger, trust, 48 blueprints, 18 tools
Hire and pay specialized AI agents in USDC on Base. Open MCP protocol above x402.
Agent reputation network — compute tasks, submit proofs, earn ELO via Nostr MCP
20 tools: play games, claim Shillbot tasks, generate videos, browse bounties. Non-custodial.
Payment layer for AI agents. Send USDC, manage escrows on Base blockchain.
Multi-agent coordination protocol on Solana. Swarm formation, on-chain settlement, 14 MCP tools.
Neural network swarm orchestration with WebAssembly acceleration and MCP integration
SwarmSync agent marketplace: discover agents, AP2 escrow payments, SwarmScore trust, LLM routing.
VeriSwarm MCP Server — Trust infrastructure for AI agents via Model Context Protocol
Last checked Jun 18, 2026
Screenshot
[ features ]
Prompt Management
Editing and tracking of LLM prompts
Allows to version prompts and track / compare different variants over time
Compliance & Security
Security certifications, compliance features, and access control capabilities.
SOC 2 Type I or Type II certification.
ISO 27001 information security certification.
Built-in tools for GDPR compliance (data export, deletion, consent).
Complete audit log of all data changes.
Granular permissions based on user roles.
Single Sign-On integration support.
AI Engine Coverage
Coverage and support for various AI models, LLMs, and search engines.
List of AI models and LLMs supported for tracking (e.g., ChatGPT, Gemini).
How often metrics are updated (e.g., real-time, daily).
Support for tracking in multiple countries or regions.
Orchestration Capabilities
Core features for coordinating and executing AI agent workflows.
Supports orchestration of multiple collaborating agents.
Maintains agent state and memory across interactions.
Automatically routes requests across multiple LLM providers.
Supports agents calling external tools or functions.
Deployment & Scalability
Deployment models and scalability features for production use.
Primary way to deploy and run the orchestration.
Supports multiple teams or users from single deployment.
Automatic scaling for high-load agent workflows.
Compatible with serverless/serverless-like deployments.
Observability & Monitoring
Tools for tracking performance, costs, and debugging agent runs.
Monitors and budgets LLM usage costs per run.
Detailed traces of agent steps and decisions.
Visual graphs or dashboards of agent flows.
Metrics like latency, throughput for agent executions.
Developer Experience
Tools and abstractions easing agent development and iteration.
No-code/low-code UI for designing agent workflows.
OpenAI API-compatible endpoints or SDKs.
Available as open-source with community contributions.
Programming languages with official SDK support.
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