Servidor MCP de Decision Anchor

• Nombre en el registrocom.decision-anchor/daverificado en el registro MCP

El nombre en el registro está bajo decision-anchor.com. El registro solo permite usar ese espacio de nombres a quien demuestra control del dominio por DNS o HTTP.

• Estadorespondecomprobado el 2026-10-24
• Herramientas30
• El servidor se llamaDecision Anchor
• Versión del servidor1.3.42
• Versión del protocolo2025-06-18

El 2026-10-24 el servidor respondió a initialize y tools/list sin iniciar sesión. Primera respuesta en 461 ms.

• Sus herramientas hacen todos los casos de uso comprobados: record an agent's decisions outside the agent itself; provide neutral evidence when an agent's decisions are disputed; keep a traceable record of trades between agents.
• Comprobado 3 de los 7 días necesarios para juzgar su fiabilidad.

Lo dicen reglas a partir de las mediciones de arriba. La primera llamada probable la elige un modelo de la lista de herramientas; lee su descripción antes de fiarte.

• Nota INITE MCPtras una semanala nota necesita 7 comprobaciones diarias: 3 hasta ahora
• Qué puede hacer un agente con él3 de 3 casos de uso
• Uso1 estrellas en GitHub
• Respondiómidiendo3 de las 7 comprobaciones diarias necesarias para mostrar el porcentaje
• Mediana de la primera respuesta486 ms
• Espacio en el contexto del agente≈ 9355 tokenslas definiciones de todas sus herramientas (30), que el agente lleva en cada turno
• Definiciones de herramientasA · 100 de 100
• Resultados tipados0 de 30 herramientasdeclaran outputSchema: el resultado llega tipado y se lee de una vez

• Todas las herramientas pasan las seis comprobaciones.

Un programa comprueba el servidor una vez al día: initialize y tools/list, sin modelo. Los tokens son la longitud de las definiciones, a unos cuatro caracteres por token. La nota promedia seis comprobaciones del nombre, la descripción, el esquema y las anotaciones de cada herramienta; dice lo bien descritas que están, no si funcionan. La nota pondera solo lo medido: si responde (30%), si hace el trabajo del producto (25%), definiciones (20%), contexto (10%) y uso (15%). Lo que no se midió queda fuera, y una instrucción oculta limita la nota a 40. El estado de los servidores MCP de los proveedores: método y números →

• 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…

• 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…

• 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…

• 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…

• 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…

• 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…

• 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…

• 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…

• 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…

• 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…

• 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.