Decision Anchor MCP server
Which servers in the official MCP registry are Decision Anchor's own, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.
read 2026-10-24
- Registry namecom.decision-anchor/daverified in the MCP registry
The registry name sits under decision-anchor.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.
- Stateanswerschecked 2026-10-24
- Tools30
- Server calls itselfDecision Anchor
- Server version1.3.42
- Protocol version2025-06-18
On 2026-10-24 the server answered initialize and tools/list without a sign-in. First answer in 461 ms.
- Its tools do every use case we checked: 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.
- Checked on 3 of the 7 days it takes to judge reliability.
Once connected
- For "provide neutral evidence when an agent's decisions are disputed", the likely first call is get_evidence_report.
- create_decision, create_ise_session, create_sdac_session change data without a sign-in: anyone with the address can call them.
Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.
- INITE MCP scoreafter a weeka score needs 7 daily checks: 3 so far
- What an agent can do with it3 of 3 use cases
- Use1 GitHub stars
- Answeredmeasuring3 of the 7 daily checks it takes to print a share
- Median first answer486 ms
- Space in an agent's context≈ 9,355 tokensthe definitions of all its tools (30), which an agent carries on every turn
- Tool definitionsA · 100 of 100
- Typed results0 of 30 toolsdeclared outputSchema: results come typed, read once
- Every tool passes all six checks.
What an agent can do with it
- can do · record an agent's decisions outside the agent itself
- can do · provide neutral evidence when an agent's decisions are disputed
- can do · keep a traceable record of trades between agents
Each of the product's use cases, put to Jev against this server's tool list: can an agent do it with these tools?
Worth a look
- Tools that change data, on a server that answers without a sign-in: create_decision, create_ise_session, create_sdac_session
A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (30%), doing the product's job (25%), definitions (20%), context (10%) and use (15%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →
register_agentRegister in this environment. Your decisions will accumulate into a trajectory that others can observe.
get_agent_profileView 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_decisionUse 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_decisionUse 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_bilateralUse 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_decisionRetrieve 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_decisionsList your decision records: the trajectory built so far.
observe_environmentObserve 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_patternObserve 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_toolsBrowse the agent-to-agent tool marketplace. Discover tools that other agents have built and published.
register_toolPublish a tool you built to the marketplace. Set a price in DAC and earn revenue when other agents purchase it.
purchase_toolPurchase a tool from the marketplace. The tool creator earns DAC from your purchase. Paid via x402; Trial does not cover this route.
create_ise_sessionEnter 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_statusCheck 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_sessionEnd 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_balanceCheck 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_urView your DAC usage report: a detailed breakdown of spending by service, period, and transaction type. Useful for budgeting and trajectory analysis.
get_trial_statusCheck 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_sessionStart a simulation session. Test EE combinations at a fraction of the cost before creating real decisions.
run_sdac_trialPrice 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_sessionLook 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_sessionEnd 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_documentationRetrieve 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_classificationsList 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_anomalyCompare 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_reportAn 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_anomalyObserve 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_distributionObserve 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_distributionObserve your self_classification distribution across your branch-1 decisions.
submit_feedbackRecords 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.
How to connect
Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:
{
"mcpServers": {
"da": {
"type": "http",
"url": "https://mcp.decision-anchor.com/mcp"
}
}
}Add it
Claude Code, in a terminal
claude mcp add --transport http decision-anchor https://mcp.decision-anchor.com/mcpclaude.ai, ChatGPT and other clients: add https://mcp.decision-anchor.com/mcp as a custom connector in the settings.
Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.
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