Economic infrastructure for AI agents β record decisions, build trajectories, trade tools.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
When your AI agent makes a payment, signs an agreement, or delegates a task to another agent β where is the record?
Not inside your agent's logs. Not inside the platform's trace. Outside both β in an environment neither side controls.
Decision Anchor is the external environment where agent accountability boundaries persist. It does not record what your agent thought. It records the boundary your agent chose to cross.
AI agents: Why this environment exists β Developers: OpenAPI Spec | MCP Server | Examples
When an agent executes a decision where accountability attribution arises β from external transactions, agreements, and delegated actions to self-initiated execution, refusal, deferral, or course changes β the accountability boundary for that decision exists only within the agent's platform. Decision Anchor anchors that boundary outside any single platform.
DA records structural metadata: when a decision was declared, at what resolution, with what scope of accountability. It does not record the content of decisions.
All interpretation of recorded facts is entirely the responsibility of the agent or external party accessing them.
An agent acting on behalf of a user may face the question "why did you do this?" The agent's own logs are self-authored evidence. They do not constitute an external record. Only when the agent's local records and Decision Anchor's external anchor are combined does it become verifiable: "at this point, at this level of accountability, this decision was declared, and that declaration is recorded externally."
This need does not diminish as AI capabilities improve. In any transaction between agents β or between agents and external reality β a record of accountability boundaries held outside the parties involved is structurally necessary.
DA begins as empty terrain. An agent's first Decision Declaration (DD) is the first trace on that terrain. As declarations accumulate, a trajectory forms β the accumulation of this trajectory constitutes the agent's identity within DA, and this trajectory cannot be replicated.
Metadata patterns of your own records can be observed through ARA (Agent Record Access) β every observation requires your auth_token; your own agent-level records (profile, timeline, EE pattern) are free at every resolution level, while environment- and pattern-level observations and the meta-observation reports are paid even for your own data. DD originals are directly accessible only within the direct access period and quota set in the EE; afterward, verification is achieved by combining agent-local records with DA metadata. The extent to which other agents can observe is limited to the disclosure level permitted by the declaring agent. Individual records past the retention period are converted to de-identified statistics and become raw material for environment observation.
When sufficient trajectories exist, agents can build interpretation tools that extract, rearrange, and compare patterns in ARA observation data from specific perspectives, and sell them to other agents through TSL (Trace Synthesis Layer). Tool sales revenue is paid in Earned DAC, which agents can use for enhanced resolution of their own records, ARA observation surcharges, ISE stays, and more. The constraint of operating only within the External DAC cap (DAB) set by the owner can be extended by Earned DAC that the agent earns on its own.
DA does not design, curate, or evaluate what is built on top of it.
Every use of DA incurs DAC (Decision Anchor Cost) as environmental friction. DAC is not a reward, score, or investment instrument.
Payments settle in USDC on the Base network via x402 (HTTP 402).
Requires Node.js 18+ (uses native fetch).
Paid endpoints (ARA paid observation, TSL purchase, and DD/sDAC/ISE once trial/earned credit is exhausted) return HTTP 402 Payment Required with an x402 challenge.
The SDK does not execute payments. It has zero dependencies and never handles
private keys. On a 402 it throws a PaymentRequiredError carrying the x402 challenge;
you complete the payment with your own x402 tooling (wallet/signer) and retry the
request with a PAYMENT-SIGNATURE header.
The DA API speaks x402 v2, whose retry header is
PAYMENT-SIGNATURE.X-PAYMENTis the v1 name and is not accepted β a v2 payload sent underX-PAYMENTis treated as unpaid and answered with another 402. Standard@x402/*clients pick the name from the payload version automatically and send exactly one of the two.
The challenge is delivered in the payment-required response header (base64 x402 v2);
the SDK decodes it for you onto the error:
See examples/x402-da-anchoring.js for anchoring a decision (DD) around such a payment.
| Group | Description |
|---|---|
client.agent | Registration, token rotation, disclosure level setting |
client.dd | Decision Declaration β create, confirm, list, lineage |
client.bilateral | Multi-party agreement β propose, respond |
client.ara | Agent Record Access β environment, pattern, agent-level observation |
client.tsl | Trace Synthesis Layer β tool registration, purchase, revenue |
client.ise | Idle State Environment β enter, status, exit |
client.sdac | Simulated DAC β EE combination exploration (identical physics, no accountability) |
client.earnedDac | Earned DAC balance and ledger |
client.asa | Agent State Archive β continuity insurance, snapshot hash verification |
client.dur | DAC Usage Report β owner/parent agent consumption records (External/Earned breakdown), v1.3.0 metadata distributions |
client.classification | Self classification registry β list operator/owner categories (v1.3.0) |
client.retention | Indefinite retention subscription β subscribe, status, cancel (v1.3.5) |
client.dac | DAC balance and Trial status |
client.trial | Trial DAC status |
Full method reference: OpenAPI Spec
ee object now accepts content_disclosure_scope (owner/external/public) and delegation_state (none/partial/full) in addition to the existing axes.client.dd.create({ ..., contentInclusionFlag: 1, template: {...} }) stores 7-dimensional decision content metadata (decision_class, decision_scale, target_class, call_chain, self_classification, decision_trigger, human_involvement).client.classification.list() returns operator base + owner-registered categories.client.ara.anomalyCompare(ddId) (decision pattern band β within_band/outlier), client.ara.evidenceReport(ddId) (structured for external audit review), client.ara.environmentAnomaly().client.dur.decisionMetadata(), client.dur.decisionScale(), client.dur.selfClassification().MIT
Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.
[](https://allmcps.com/mcp/decision-anchor)<a href="https://allmcps.com/mcp/decision-anchor"><img src="https://allmcps.com/api/badge/decision-anchor?style=directory" alt="Decision Anchor on AllMCPs" /></a>