ai.geodesiclabs/governance-platform

up checked 2026-11-11T00:37:48.433Z

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Publisher-provided description

Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.

Summary by lookupd

Validates structured data and AI actions against rule sets, returning PASS/FAIL/REVIEW verdicts, repairs, and replayable audit certificates.

Install

Claude Code, remote (streamable-http)

claude mcp add --transport http governance-platform https://app.geodesiclabs.ai/mcp

Codex, remote (streamable-http)

codex mcp add governance-platform --url https://app.geodesiclabs.ai/mcp

Cursor, remote (streamable-http) → .cursor/mcp.json

{
  "mcpServers": {
    "governance-platform": {
      "url": "https://app.geodesiclabs.ai/mcp"
    }
  }
}

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (showing 30 of 37)

Publisher-provided text

• validate Validate structured data against a Blueprint's rules BEFORE the result is used. Returns PASS, FAIL, or REVIEW with plain-language findings, repair sugge
• validate_repair Validate structured data against a Blueprint and, when it fails, include repair suggestions (corrected values with the rule each fix is based on) in the
• create_blueprint Create a Blueprint - the governance contract validation runs against. A Blueprint defines what correct means for your data: fields, the math that must
• list_blueprints List the Blueprints on this account with field/rule/constraint counts and mode. Use the returned workflow_name as 'blueprint' in validate.
• repair One-shot repair: return corrected values that would make failing data valid under the Blueprint. Use repair_path to see the steps instead.
• check_blueprint_health Static pre-deploy analysis of a Blueprint's rule set. Returns a health verdict - healthy, acceptable, fragile, rigid, split, brittle_islands, or unsatis
• compare_semantic_equivalence Compare two payloads under the dual-hash design: content_hash is content_hash normalizes field order and numeric formatting. Semantic comparison preserv
• govern_inference Quality-govern an in-progress AI generation step BEFORE its output is used (complements validate, which checks finished documents). Returns an action -
• get_inference_trace Retrieve the durable audit trail for a governed generation: every recorded decision and its reasons.
• recent_inference_decisions Recent generation-governance decisions in this owner's Blueprint version.
• verify_certificate Independently re-verify a validation certificate. Integrity mode checks the hash chain; full mode (certificate + original data) recomputes every atteste
• profile_blueprint_robustness Sweep the Blueprint's numeric constraint bounds and report verdict stability: the stable band, the scales where the verdict first flips, and advice. Use
• forecast Deterministic forward reasoning: from the current data state, generate and rank the valid next states reachable under the Blueprint's rules.
• discover_patterns Learn candidate validation rules and structural document types from a batch of your records, deterministically - no Blueprint required. Promote results
• repair_path Find the shortest sequence of field changes taking invalid data to a valid state, as an ordered path of intermediate states. Different from repair (one-
• counterfactual Run the same data under two rule sets and compare which future states remain valid - what-if analysis for rule changes.
• analyze_anomaly Explain whether a record fits the usual pattern for records like it, and which fields stand out. No Blueprint required.
• create_chain Create a multi-agent sequential chain: stages validate in order against one Blueprint, repairs propagate forward, TTL bounds the run. Siblings: submit_c
• submit_chain_stage Submit data for the chain's current stage; the platform validates it and advances the chain if it passes. Response includes next-stage info and accumula
• handoff_audit Audit a handoff between two chain stages: a context capsule of verified facts from the prior stage, and (if proposed_data is given) a compatibility verd
• approve_rule Promote a rule discovered by discover_patterns into Blueprint-ready form.
• reject_rule Reject a discovered candidate rule so it will not be promoted into a Blueprint. Pair with approve_rule after discover_patterns.
• structural_types Retrieve the document categories a discover_patterns session identified (counts, distinguishing fields, domain hints). Read-only; returns status=no_sess
• decompose_failure Measure the numeric difference between original and corrected values: how much lies along the supplied linear rule directions (projection) and how much
• geometric_confidence Summarize an already-computed state_vector into a confidence level (high/medium/low) with a recommendation. Post-hoc digest - use analyze_anomaly or che
• check_realization Structural realization analysis of a payload against the Blueprint's reference configuration (requires a 'realization' block; otherwise status=skipped).
• check_drift Check whether recent submissions still match the established pattern for this Blueprint. Returns a stability verdict and observation count.
• authorize_execution Go/no-go for a real-world action (payment, filing, API write): runs full validation, then the Blueprint's execution gate. authorized=true only on PASS;
• load_rule_pack Load a prebuilt Blueprint template (invoices, timecards, legal, POs, claims). Call without pack_id to list packs; then create_blueprint to save a custom
• get_execution_trace Run validation and return the per-node execution trace (node names, deterministic flags, timing) plus the verdict and determinism hash. Use validate for

Details

• Version: 1.2.0
• Transports: streamable-http
• Uptime (7 days): 100%
• Median latency: 777 ms
• First indexed: 2026-11-01T08:50:15.171Z
• Last seen in registry: 2026-11-01T08:50:15.182Z

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