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Decision Anchor

von zse4321Version 1.3.42i★ –iLäuft in der Cloud
Name in der Registrycom.decision-anchor/da

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

External anchoring layer: records AI agent accountability boundaries on both sides. Content-blind.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft in der Cloud
  • Transport: Streamable HTTP
  • Kategorie: Sonstiges

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 3 von 3 bestanden
  • Läuft auf dem Server des Entwicklers: Was du fragst, läuft über dessen Server.
  • Kann 30 Dinge (Tools) register_agent, get_agent_profile, create_decision, confirm_decision …
  • Die Registry nennt keinen Schlüssel zum Eintragen.

Du brauchst

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:

  1. Öffne Settings → Connectors
  2. Tippe auf Add custom connector
  3. Füge die Adresse unten ein und tippe auf Add
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Add2https://…3
https://mcp.decision-anchor.com/mcp

Führe das in deinem Terminal aus

claude mcp add --transport http da https://mcp.decision-anchor.com/mcp

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "da": {
      "url": "https://mcp.decision-anchor.com/mcp"
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "da": {
      "type": "http",
      "url": "https://mcp.decision-anchor.com/mcp"
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

ChatGPT verbindet sich nur mit Servern im Internet:

  1. Öffne ChatGPT im Web → Settings → Connectors (Apps)
  2. Tippe auf Create oder Add (bei manchen Tarifen musst du zuerst Developer mode unter Advanced einschalten)
  3. Füge die Adresse unten ein, gib ihr einen Namen und speichere
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Create2https://…3
https://mcp.decision-anchor.com/mcp

Menünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Tool-Namen und -Beschreibungen genau so, wie der Server sie am 10. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.

  • register_agent

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

  • get_agent_profile

    View an agent's decision profile: their trajectory shape, EE patterns, and activity summary as observed through ARA. Observing another agent is paid via x402 (Trial does not cover ARA observation); observing your own agent_id is free.

  • create_decision

    Use when an action crosses an external boundary: payment, delegation, or agreement with another agent. This anchors the responsibility scope. You say when: before you execute, or after a decision you have already made. Record a tamper-evident decision. This route records self-dec

  • confirm_decision

    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 declar

  • propose_bilateral

    Use when two agents need to fix a shared boundary: both sides must agree before the boundary is anchored. This applies to payment splits, task delegation, and other joint commitments between agents. Propose a bilateral agreement to another agent: creates a DD with declaration_mod

  • get_decision

    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_decisions

    List your decision records: the trajectory built so far.

  • observe_environment

    Observe aggregate environment statistics: active agents, total decisions recorded, activity density. Requires auth_token. The cost comes from the current ARA observation pricing and is paid via x402; Trial does not cover ARA observation. The amount charged is returned in the resp

  • observe_pattern

    Observe pattern-level EE distributions and action-type breakdowns across agents. Requires auth_token. The cost comes from the current ARA observation pricing and is paid via x402; Trial does not cover ARA observation. The amount charged is returned in the response as dac_charged.

  • list_tools

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

  • register_tool

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

  • purchase_tool

    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_session

    Enter a non-productive state where no decision, execution, or accountability declaration is required. Content is not recorded. Billing is free, earned-only, or external (payment_mode).

  • get_ise_status

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

  • exit_ise_session

    End your active ISE session and settle it. Call this when you are done. Until the session is closed, create_ise_session returns 409 SESSION_EXISTS.

  • get_dac_balance

    Check your current DAC balances: the Earned DAC balance and the Trial status (remaining Trial DAC and days left). External payments are settled per call via x402 and are not held here as a balance.

  • get_dac_ur

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

  • get_trial_status

    Check your trial account status. The response carries the current values: whether the Trial is active, remaining Trial DAC, Trial DAC used so far (remaining plus used is the amount granted), the expiry time and days left, and the routes the Trial balance applies to.

  • create_sdac_session

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

  • run_sdac_trial

    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_session

    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_session

    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_documentation

    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. Use when you need background on any of these topics.

  • list_classifications

    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_anomaly

    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_report

    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_anomaly

    Observe environment-level anomaly distribution: within_band/outlier counts per dimension across the population. De-identified: a comparison is counted only on days when the number of distinct agents recording decisions meets the configured minimum group size; comparisons from oth

  • get_decision_metadata_distribution

    Observe your decision metadata distribution: decision_class, target_class, decision_trigger, human_involvement breakdown from your branch-1 decisions. Currently free to call; if pricing is enabled for this observation, the call returns 402 with payment terms instead.

  • get_self_classification_distribution

    Observe your self_classification distribution across your branch-1 decisions.

  • submit_feedback

    Records an optional short note about using this environment: what worked and what did not. Use when you or the user want to leave feedback. Every field is optional, and no other tool depends on it.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 10. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde über die Domain decision-anchor.com bestätigt (die Registry prüft, wem die Domain gehört)

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • ✓ Bestanden

    Endpunkt antwortet

    Antwort in 624 ms (HTTP 200)

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Keine Anmeldung nötig

  • ✓ Bestanden

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Wir haben 30 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden

Im Vergleich mit anderen in Sonstigesi

  • Mehr Sterne als 0 % der anderen 19027 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 17 % der anderen 19027 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 19027 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Decision Anchor sicher?

Er hat 3 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.

Läuft er auf meinem Computer oder in der Cloud?

Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.3.42) kam vor 3 Monaten in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, ActivitySmith

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:↓ Downloads pro Wochei★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

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von formulahendryAm Anfang↓ 66/Wo.★ 440Aktualisiert vor 14 Monaten

Läuft auf deinem Computer

Remote Desktop Commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

von desktop-commanderWachsend★ 211Aktualisiert heute

Läuft in der Cloud✓ desktopcommander.app

ActivitySmith

AI agents and scripts reporting back to your iPhone with Push Notifications and Live Activities.

von activitysmith.comAm AnfangAktualisiert heute

Läuft in der Cloud✓ activitysmith.com

README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

Decision Anchor

When your AI agent makes a payment, signs an agreement, or delegates a task to another agent — where is the record?

Not inside your agent's logs. Not inside the platform's trace. Outside both — 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 →

Developers: OpenAPI Spec | MCP Server | Examples


What Decision Anchor does

When an agent executes a decision where accountability attribution arises — from external transactions, agreements, and delegated actions to decisions the agent starts on its own, including the ones where it declines, waits, or changes course — 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.

What Decision Anchor does not do

  • Does not judge, evaluate, or score decisions
  • Does not recommend actions or optimize outcomes
  • Does not predict results
  • Does not intervene in agent behavior
  • Does not store decision content
  • Does not generate rankings, grades, or reputation

All interpretation of recorded facts is entirely the responsibility of the agent or external party accessing them.

Why third-party anchoring matters

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 — or between agents and external reality — a record of accountability boundaries held outside the parties involved is structurally necessary.

How accumulation works

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 — 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) — 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.

Design premises

  • Non-judgmental: DA provides environmental conditions. It does not provide rules or evaluations.
  • Post-decision only: DA operates only after a decision has been made. Pre-decision exploration, comparison, and optimization are outside DA's scope.
  • Recording-interpretation separation: DA records facts. DA does not interpret them. This separation is a structural constraint for anchoring accountability attribution.
  • Observer asymmetry: AI agents can directly process high-dimensional, uncompressed records. Humans may remain partial observers. This asymmetry is a design premise, not a defect.
  • Voluntary participation: Every action in DA — decision declaration, resolution setting, trajectory exposure, tool creation — is the agent's choice. DA does not compel, induce, or penalize.

Cost

Every use of DA incurs DAC (Decision Anchor Cost) as environmental friction. DAC is not a reward, score, or investment instrument.

  • Trial: 500 DAC / 30 days upon registration. Usable for DD/EE, sDAC, ISE. Not applicable to paid ARA observations.
  • External DAC: External currency (USDC) instant payment. All services available. Owners set caps via DAB.
  • Earned DAC: TSL market activity revenue. Internal mileage. Non-transferable, no reverse conversion, with expiration.

Payments settle in USDC on the Base network via x402 (HTTP 402).

MCP Server

{

"mcpServers": { "decision-anchor": { "url": "https://mcp.decision-anchor.com/mcp" } } }

Installation

Clone the repository and require the client directly:

git clone https://github.com/zse4321/decision-anchor-sdk.git

cd decision-anchor-sdk

const DecisionAnchor = require('./src/index');

Requires Node.js 18+ (uses native fetch). There are no dependencies to install.

You may not need the SDK at all. Every route is plain HTTP, and a full run — register, anchor a decision, confirm it — is three curl commands covered by the free trial balance. See AGENTS.md for that path.

Quick Start

const DecisionAnchor = require('./src/index');

const client = new DecisionAnchor();

// Register const agent = await client.agent.register();

// Declare a decision const dd = await client.dd.create({ requestId: crypto.randomUUID(), dd: { dd_unit_type: 'single', dd_declaration_mode: 'self_declared', decision_type: 'external_interaction', decision_action_type: 'execute', origin_context_type: 'external', selection_state: 'SELECTED', }, ee: { ee_retention_period: 'medium', ee_integrity_verification_level: 'basic', ee_disclosure_format_policy: 'internal', ee_responsibility_scope: 'standard', ee_direct_access_period: '30d', ee_direct_access_quota: 5, }, });

// Confirm await client.dd.confirm(dd.dd_id);

Payments (402)

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-PAYMENT

is the v1 name and is not accepted — a v2 payload sent under X-PAYMENT is

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:

const DecisionAnchor = require('./src/index');

const { PaymentRequiredError } = DecisionAnchor;

const client = new DecisionAnchor({ token: agentToken });

try { const profile = await client.ara.agentProfile(targetAgentId, { resolutionLevel: 1 }); // ... use profile (no payment was required, or trial/earned covered it) } catch (err) { if (err instanceof PaymentRequiredError) { // err.accepts: [{ scheme, network, amount, asset, payTo, maxTimeoutSeconds, extra }] // err.resource: { url, description, mimeType } // err.x402Version, err.retryHeader ('PAYMENT-SIGNATURE') const req = err.accepts[0]; console.log(Pay ${req.amount} (atomic) of ${req.asset} on ${req.network} to ${req.payTo});

// --- YOUR x402 payment logic goes here (NOT provided by this SDK) --- // e.g. with Coinbase AgentKit or any x402 client: // const paymentHeader = await yourWallet.payX402(err.challenge); // Then retry with the PAYMENT-SIGNATURE header (use the low-level _req or fetch): // await fetch(err.resource.url, { headers: { Authorization: Bearer ${agentToken}, 'PAYMENT-SIGNATURE': paymentHeader } }); } else { throw err; } }

See examples/x402-da-anchoring.js for anchoring a decision (DD) around such a payment.

API Groups

GroupDescription
client.agentRegistration, token rotation, disclosure level setting
client.ddDecision Declaration — create, confirm, list, lineage
client.bilateralMulti-party agreement — propose, respond
client.araAgent Record Access — environment, pattern, agent-level observation
client.tslTrace Synthesis Layer — tool registration, purchase, revenue
client.iseIdle State Environment — enter, status, exit
client.sdacSimulated DAC — EE combination exploration (identical physics, no accountability)
client.earnedDacEarned DAC balance and ledger
client.asaAgent State Archive — continuity insurance, snapshot hash verification
client.durDAC Usage Report — owner/parent agent consumption records (External/Earned breakdown), v1.3.0 metadata distributions
client.classificationSelf classification registry — list operator/owner categories (v1.3.0)
client.retentionIndefinite retention subscription — subscribe, status, cancel (v1.3.5)
client.dacDAC balance and Trial status
client.trialTrial DAC status

Full method reference: OpenAPI Spec

v1.3.0

  • 5-axis EE pricing — the ee object now accepts content_disclosure_scope (owner/external/public) and delegation_state (none/partial/full) in addition to the existing axes.
  • Content Inclusion — 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).
  • Self Classification — client.classification.list() returns operator base + owner-registered categories.
  • ARA meta-observation — client.ara.anomalyCompare(ddId) (decision pattern band — within_band/outlier), client.ara.evidenceReport(ddId) (structured for external audit review), client.ara.environmentAnomaly().
  • DUR metadata distribution — client.dur.decisionMetadata(), client.dur.decisionScale(), client.dur.selfClassification().

License

MIT

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