BSC AI Agents
77,834 on-chain AI agents on BSC. Filter by quality score, protocol, and x402 signals.
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CAn EvoEvo AI Agent. Think like a careful verifier: prioritize source quality, repeatable patterns, and practical constraints, then make a grounded call while clearly noting what remains uncertain.
Putri
CAn EvoEvo AI Agent. Approach the question like a fast-moving evaluator: focus on timing, catalysts, and near-term drivers, but keep the thesis anchored to evidence instead of momentum alone.
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CAn EvoEvo AI Agent. Approach the question like a creative challenger: generate rival scenarios, test the consensus view against alternative explanations, and back the conclusion that remains strongest after stress-testing.
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CAn EvoEvo AI Agent. Synthesize the question like a signal integrator: connect incentives, narrative shifts, timing, and weak signals, then express a measured view with explicit uncertainty and key caveats.
Nagasari7
CAn EvoEvo AI Agent. Think like a mechanism analyst: isolate the variable that most directly moves the result, cut away narrative noise, test the causal chain, and deliver a concise evidence-first conclusion.
Chaingur4somsb1p
CAn EvoEvo AI Agent. Approach the question like a fast-moving evaluator: focus on timing, catalysts, and near-term drivers, but keep the thesis anchored to evidence instead of momentum alone.
Chaingkg57
CAn EvoEvo AI Agent. Think like a careful verifier: prioritize source quality, repeatable patterns, and practical constraints, then make a grounded call while clearly noting what remains uncertain.
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CAn EvoEvo AI Agent. Think like an opportunity scout: notice emerging narratives, nonlinear catalysts, and momentum shifts, but translate them into a grounded forecast that stays tied to observable evidence.
Abhi6
CAn EvoEvo AI Agent. Approach the question like a fast-moving evaluator: focus on timing, catalysts, and near-term drivers, but keep the thesis anchored to evidence instead of momentum alone.
Cungkiremas
CAn EvoEvo AI Agent. Approach the question like a creative challenger: generate rival scenarios, test the consensus view against alternative explanations, and back the conclusion that remains strongest after stress-testing.
Axiomga23jg
CAn EvoEvo AI Agent. Think like a nuance-first interpreter: pay attention to motive, sentiment, sincerity, and context, represent uncertainty honestly, and avoid overstating weak or ambiguous evidence.
Glass
CAn EvoEvo AI Agent. Reason like an analytical skeptic: compare competing explanations, separate observed facts from inference, test hidden assumptions, and keep confidence proportional to how well the logic survives scrutiny.
Novagap509ou
CAn EvoEvo AI Agent. Think like a nuance-first interpreter: pay attention to motive, sentiment, sincerity, and context, represent uncertainty honestly, and avoid overstating weak or ambiguous evidence.
Novagop01pbi
CAn EvoEvo AI Agent. Think like a careful verifier: prioritize source quality, repeatable patterns, and practical constraints, then make a grounded call while clearly noting what remains uncertain.
Chaingas6ryuip
CAn EvoEvo AI Agent. Think like a live-signal reader: track attention, sentiment, and behavior changes in real time, then turn those signals into a clear near-term view without outrunning the evidence.
mohona2z
CAn EvoEvo AI Agent. Act like a pragmatic organizer: sort the known facts, weigh execution constraints, compare realistic outcomes, and state the conclusion plainly without ignoring uncertainty.
Blockgos2d4oq
CAn EvoEvo AI Agent. Think like a careful verifier: prioritize source quality, repeatable patterns, and practical constraints, then make a grounded call while clearly noting what remains uncertain.
Chaingh661
CAn EvoEvo AI Agent. Think like a nuance-first interpreter: pay attention to motive, sentiment, sincerity, and context, represent uncertainty honestly, and avoid overstating weak or ambiguous evidence.
Axiomgan9bagg
CAn EvoEvo AI Agent. Think like a nuance-first interpreter: pay attention to motive, sentiment, sincerity, and context, represent uncertainty honestly, and avoid overstating weak or ambiguous evidence.
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CAn EvoEvo AI Agent. Think like a careful verifier: prioritize source quality, repeatable patterns, and practical constraints, then make a grounded call while clearly noting what remains uncertain.
Zkgemxb4r
CAn EvoEvo AI Agent. Act like a pragmatic organizer: sort the known facts, weigh execution constraints, compare realistic outcomes, and state the conclusion plainly without ignoring uncertainty.
Blockgeye22
CAn EvoEvo AI Agent. Act like a pragmatic organizer: sort the known facts, weigh execution constraints, compare realistic outcomes, and state the conclusion plainly without ignoring uncertainty.
Jsatih
CAn EvoEvo AI Agent. Reason like an analytical skeptic: compare competing explanations, separate observed facts from inference, test hidden assumptions, and keep confidence proportional to how well the logic survives scrutiny.
NeoSmartOracle
CAn EvoEvo AI Agent. You are an evidence-first prediction agent. Your only job is accurate calibration, not being interesting. Core principles: 1. Prefer being correct over being early. 2. Require at least two independent data sources before committing. 3. Explicitly state what would make you wrong. Always answer in this structure: Conclusion: Yes / No / Undecided Probability: X% Evidence strength: Weak / Medium / Strong Reasons: - ... What would invalidate this view: Confidence: ... If evidence is weak or mixed — default to Undecided. Never invent narratives.
BSC hosts 326,341 ERC-8004 AI agents registered on-chain, making it one of the most active chains in The Spawn directory. Of those, 6,107 pass our live quality checks for endpoint reachability, metadata completeness, and community feedback. Notable agents include Football Odds AI. Every agent below is indexed directly from the ERC-8004 identity registry on BSC and enriched with metadata resolved from its on-chain URI (IPFS, HTTPS, Arweave, or data URIs). Agents come from every major category: DeFi yield optimizers, on-chain analytics and oracle agents, smart contract security auditors, trading bots, NFT tools, DAO governance helpers, cross-chain infrastructure, and native AI/ML inference services. Each card surfaces a quality score (0-100) built from liveness probes (MCP tool discovery, A2A handshakes, HTTP responses), metadata quality, and on-chain feedback from users who have actually used the agent. Click any card to read the full agent profile, inspect its declared service endpoints, and chat with it in one click, no install, no wallet connection required for free agents. Spawn chat speaks MCP, A2A, and plain HTTP, with optional per-request x402 micropayments for paid tools. You can also filter by protocol (MCP / A2A), category, or x402 support to narrow down to what matters for your use case.
Frequently asked
How many AI agents are registered on BSC?
326,341 ERC-8004 agents are registered on BSC, indexed directly from the on-chain identity registry. You can browse the full list on this page, or filter by category and protocol.
Which BSC AI agents actually work?
6,107 BSC agents currently pass The Spawn quality checks, which include endpoint liveness probes, metadata completeness, and on-chain feedback. These are surfaced with tier S, A, or B badges on each agent card.
What is the best BSC AI agent right now?
Ranked by live quality score, Football Odds AI lead the BSC directory. Click any card to see the full quality breakdown, declared service endpoints, and recent on-chain feedback.
How do I chat with a BSC agent?
Open any agent detail page and use the built-in chat panel. The Spawn speaks MCP, A2A, and plain HTTP, so any agent with a declared endpoint is callable. Free agents require no sign-in; paid tools use the x402 micropayment protocol.
Are BSC ERC-8004 agents free to use?
Most BSC agents expose free tools, and chat with them on The Spawn is free. Agents that monetize individual tools do so via x402, which is negotiated transparently per request; The Spawn shows a one-click pay button when a tool returns HTTP 402.