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PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

Decision Anchor

de zse4321versión 1.3.42i★ 1iSe ejecuta en la nube
Nombre en el registrocom.decision-anchor/da

Instalar

Resumen

Descripción del creador (original en inglés)

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

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en la nube
  • Transporte: Streamable HTTP
  • Categoría: Otros

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Necesitas

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Funciona en Claude para web, escritorio y móvil:

  1. Abre Settings → Connectors
  2. Presiona Add custom connector
  3. Pega la dirección de abajo y presiona Add
  4. Si te pide iniciar sesión, inicia sesión en el servicio del creador
SettingsConnectors1+ Add2https://…3Connect4
https://mcp.decision-anchor.com/mcp

Ejecuta esto en tu terminal

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

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

ChatGPT solo se conecta a servidores en internet:

  1. Abre ChatGPT en la web → Settings → Connectors (Apps)
  2. Presiona Create o Add (en algunos planes primero hay que activar Developer mode en Advanced)
  3. Pega la dirección de abajo, ponle un nombre y guarda
  4. Si te pide iniciar sesión, inicia sesión en el servicio del creador
SettingsConnectors1+ Create2https://…3Connect4
https://mcp.decision-anchor.com/mcp

Los nombres de los menús pueden variar un poco según el plan y con el tiempo.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué apps pueden usarlo

Según cómo se conecta este servidor y la documentación de cada app, comprobado el 10 nov 2026.

Se conectan por internet en

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

Todas las apps, con ventajas y desventajas →

Qué puede hacer

Nombres y descripciones de las herramientas tal como los informó el servidor el 10 nov 2026. Los escribió el creador, no nosotros; los mostramos como texto sin formato.

  • 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.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 11 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con el dominio decision-anchor.com (el registro comprueba quién es dueño del dominio)

  • ✓ Superada

    Sigue en mantenimiento

    Último cambio de código: hace 2 meses

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • ✓ Superada

    El endpoint responde

    Respondió en 624 ms (HTTP 200)

  • – No aplica

    Inicio de sesión con OAuth

    No hace falta iniciar sesión

  • ✓ Superada

    Sin instrucciones ocultas en las descripciones de herramientas

    Leímos 30 descripciones de herramientas y no encontramos instrucciones ocultas para la IA

Comparado con otros en Otrosi

  • Más estrellas que el 82% de los otros 19107 servidores de esta categoría
  • Publicado en el registro más recientemente que el 17% de los otros 19107 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 19107 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Decision Anchor?

Superó 4 de 4 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez hace 2 meses, y la última versión (1.3.42) llegó al registro hace 3 meses.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.

¿Qué puedo usar en su lugar?

En la misma categoría: World Monitor, Claude Flow, Tldraw

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.

de koala73Muy usado★ 90,4 milActualizado hace 6 días

Se ejecuta en la nube✓ worldmonitor.app

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

de ruvnetMuy usado↓ 13,5 mil/sem★ 81,4 milActualizado hace 14 meses

Se ejecuta en tu computadora

Tldraw

Draw and visually collaborate with your agents on tldraw's canvas.

de tldrawMuy usado★ 51,4 milActualizado hace 8 meses

Se ejecuta en la nube

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

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