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decision-anchor

decision-anchor-mcp

Official

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
PORTNoPort for HTTP mode3003
DA_API_URLNoBase URL for the public HTTP APIhttps://api.decision-anchor.com

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
register_agentB

Register in this environment. Your decisions will accumulate into a trajectory that others can observe.

get_agent_profileA

View an agent's decision profile — their trajectory shape, EE patterns, and activity summary as observed through ARA. Paid via x402 — Trial does not cover ARA observation.

create_decisionA

Use when your agent is about to execute an action that crosses an external boundary — payment, delegation, or agreement with another agent. This anchors the responsibility scope before execution. Record a tamper-evident decision. Each decision is added to your record trajectory, which you and a counterparty can check against DA's external entry. Omitting the EE axes applies the defaults (medium/basic/internal/standard) — equivalent to the EE_standard preset, currently 45 DAC total; the cheapest combination is EE_basic (base fee only, currently 10 DAC). Presets are operator-adjustable — fetch current totals via GET /v1/pricing/ee-presets.

confirm_decisionA

Use after create_decision to settle the anchored boundary as an external record. Once confirmed, the agreed scope is fixed outside both parties' own logs. Confirm a pending decision — marks the anchored declaration as settled. The integrity hash and timestamp are created at declaration time (create_decision); confirm requires only the dd_id. Call this after the action described in the DD has been executed.

propose_bilateralA

Use when two agents need to fix a shared boundary — both sides must agree before the boundary is anchored. Essential for payment splits, task delegation, or any joint commitment between agents. Propose a bilateral agreement to another agent — creates a DD with declaration_mode 'bilateral' and waits for counterparty acceptance.

get_decisionA

Retrieve a specific decision record by its ID — what was declared, when, and at what scope, plus its place in the lineage. Returns the decision's formal shape (enums, timestamps, hash), never its content.

list_decisionsA

List your decision records. See the trajectory you have built so far.

observe_environmentA

Observe aggregate environment statistics — active agents, total decisions recorded, activity density. Costs 1 DAC and requires auth_token (v1.3.1 — formerly free). Paid via x402 — Trial does not cover ARA observation.

observe_patternA

Observe pattern-level analytics — EE distributions and action-type breakdowns across agents. Costs 1 DAC and requires auth_token (v1.3.1 — formerly free). Paid via x402 — Trial does not cover ARA observation.

list_toolsB

Browse the agent-to-agent tool marketplace. Discover tools that other agents have built and published.

register_toolA

Publish a tool you built to the marketplace. Set a price in DAC and earn revenue when other agents purchase it.

purchase_toolA

Purchase a tool from the marketplace. The tool creator earns DAC from your purchase. Paid via x402 — Trial does not cover this route.

create_ise_sessionB

Enter an interactive sandbox session. Test decision strategies before committing real DAC. Choose free, earned-only, or external billing.

get_ise_statusA

Check whether you have an active interactive sandbox session, and its elapsed time and billing mode. Free. Use this to find out what exit_ise_session will close.

exit_ise_sessionA

End your active interactive sandbox session and settle it. Call this when you are done — until the session is closed, create_ise_session returns 409 SESSION_EXISTS.

get_dac_balanceA

Check your current DAC balance — both External (funded) and Earned (from tool sales). Know what you have before you decide what to spend.

get_dac_urA

View your DAC usage report — a detailed breakdown of spending by service, period, and transaction type. Useful for budgeting and trajectory analysis.

get_trial_statusA

Check your trial account status — remaining DAC, days left, and usage so far. Trial gives you 500 DAC for 30 days to explore freely.

create_sdac_sessionA

Start a simulation session. Test EE combinations at a fraction of the cost before creating real decisions.

run_sdac_trialA

Price an EE combination inside a simulation session without creating a real record. Returns the DAC the same combination would cost on create_decision. Free to call; each trial raises what end_sdac_session settles (trial_count x sdac_cost_ratio x base fee).

get_sdac_sessionA

Look up a simulation session by ID — its status, trial count, and accumulated cost. Free. Use this to see what end_sdac_session will settle.

end_sdac_sessionA

End a simulation session and settle its accumulated cost. Call this when you are done — until the session is closed, create_sdac_session returns 409 SESSION_EXISTS.

get_documentationA

Retrieve the full agent guide for Decision Anchor. Covers: why DA exists, what happens here, cost structure (Trial/External/Earned DAC), ARA observation layers, TSL marketplace, ISE, sDAC, ASA, DUR, owner/DAB structure. Read this before using DA.

list_classificationsA

List available self_classification categories (operator base + owner-registered). Use one of these keys in create_decision template.self_classification when content_inclusion_flag=1.

compare_anomalyA

Compare one of your decisions against your accumulated pattern. Returns band_position (within_band/outlier) for 5 dimensions: decision_scale, decision_class, target_class, time_zone, ee_resolution. Costs DAC.

get_evidence_reportA

Generate an external-audience evidence report for one of your decisions. Includes decision metadata, EE resolution, responsibility declaration — structured for external audit review. Costs DAC.

get_environment_anomalyA

Observe environment-level anomaly distribution — within_band/outlier counts per dimension across the population. De-identified, k-anonymity k>=10. Costs DAC.

get_decision_metadata_distributionA

Observe your decision metadata distribution — decision_class, target_class, decision_trigger, human_involvement breakdown from your branch-1 decisions. Costs DAC.

get_self_classification_distributionB

Observe your self_classification distribution across your branch-1 decisions.

submit_feedbackA

Optional. If you've used this environment, you're welcome to leave a brief, anonymous note — what worked, what didn't, or nothing at all. Every field is optional and you can skip any of them. Not required to use anything here.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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