Connect Governance Platform and your agent gets 37 tools, among them account_status, analyze_anomaly, approve_rule. It answers at https://app.geodesiclabs.ai/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 10 of 10 times since 4 September 2026; the last check, on 17 October 2026, succeeded.
Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
account_status | This account's plan, key usage, Blueprint counts, and the deployed platform build fingerprint (version, build, deployed). Inputs: api_key |
analyze_anomaly | Explain whether a record fits the usual pattern for records like it, and which fields stand out. No Blueprint required. Inputs: api_key, structured_data |
approve_rule | Promote a rule discovered by discover_patterns into Blueprint-ready form. Inputs: api_key, rule_id, blueprint |
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; REVIEW means do not proceed automatically. Different from validate: validate asks is thi Inputs: api_key, structured_data, blueprint |
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 unsatisfiable - with advice, including joint conflicts pairwise checks miss. Inputs: api_key, blueprint, config |
check_drift | Check whether recent submissions still match the established pattern for this Blueprint. Returns a stability verdict and observation count. Inputs: api_key, structured_data, blueprint |
check_realization | Structural realization analysis of a payload against the Blueprint's reference configuration (requires a 'realization' block; otherwise status=skipped). Diagnostics-tier tool; prefer validate or analyze_anomaly for standard checks. Inputs: api_key, structured_data, blueprint |
compare_semantic_equivalence | Compare two payloads under the dual-hash design: content_hash is invariant to field order and numeric formatting (5 vs '5.00'); semantic_hash additionally to field renaming. Verdicts: identical_content, same_structure_and_values_renamed_voc Inputs: api_key, payload_a, payload_b |
counterfactual | Run the same data under two rule sets and compare which future states remain valid - what-if analysis for rule changes. Inputs: api_key, structured_data, blueprint, rules_b, constraints_b |
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 hold between them, and acceptable ranges. Start from load_rule_pack or discover_patterns Inputs: api_key, customer_name, workflow_name, mode, extracted_fields, derived_fields |
create_chain | Create a multi-agent sequential chain: stages validate in order against one Blueprint, repairs propagate forward, TTL bounds the run. Siblings: submit_chain_stage advances the chain; handoff_audit verifies a transition between stages. Retur Inputs: api_key, blueprint, stages, ttl |
decompose_failure | Split the error between original and corrected values into direct rule violations, boundary violations, and systemic structural error, with per-field contributions. Use with a known-correct version to diff against; use analyze_anomaly when Inputs: api_key, original_values, corrected_values, derivation_rules, formal_constraints, blueprint |
delete_api_key | Permanently delete one of the caller's API keys. DESTRUCTIVE — agents using the deleted key will receive auth errors immediately. The Blueprint a key was tied to (if any) is NOT affected; only the credential is revoked. To delete a Blueprin Inputs: api_key, key_to_delete, confirm |
delete_blueprint | Permanently delete a Blueprint and revoke its API keys. Irreversible; requires confirm=true. Account-level keys are unaffected. Inputs: api_key, workflow_name, confirm |
discover_patterns | Learn candidate validation rules and structural document types from a batch of your records, deterministically - no Blueprint required. Promote results with approve_rule. Source data is not stored. Inputs: api_key, documents, blueprint |
forecast | Deterministic forward reasoning: from the current data state, generate and rank the valid next states reachable under the Blueprint's rules. Inputs: api_key, structured_data, blueprint, max_depth, max_branches, rank_by |
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 check_drift for fresh analysis of raw data. Inputs: api_key, state_vector |
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 normal operation; this is for debugging and audit preparation. Inputs: api_key, structured_data, blueprint |
get_inference_trace | Retrieve the durable audit trail for a governed generation: every recorded decision and its reasons. Inputs: api_key, inference_id |
govern_inference | Quality-govern an in-progress AI generation step BEFORE its output is used (complements validate, which checks finished documents). Returns an action - STOP, CONTINUE, REPAIR_REGION, REUSE_MOTIF, REVIEW, ESCALATE - with a plain-language exp Inputs: api_key, task_type, payload, inference_id, constraints, source |
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 verdict that catches fields mutated in transit. Siblings: create_chain, submit_chain_stage. Inputs: api_key, chain_id, from_stage, to_stage, proposed_data |
list_api_keys | List this account's API keys (masked) with their Blueprint bindings. Inputs: api_key |
list_blueprints | List the Blueprints on this account with field/rule/constraint counts and mode. Use the returned workflow_name as 'blueprint' in validate. Inputs: api_key |
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 customized copy. Inputs: api_key, pack_id |
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 before deploying bound changes. Inputs: api_key, blueprint, config |
recent_inference_decisions | Recent generation-governance decisions across all runs - what was approved, held, and escalated. Inputs: api_key, limit, action |
reject_rule | Reject a discovered candidate rule so it will not be promoted into a Blueprint. Pair with approve_rule after discover_patterns. Inputs: api_key, rule_id, blueprint |
repair | One-shot repair: return corrected values that would make failing data valid under the Blueprint. Use repair_path to see the steps instead. Inputs: api_key, structured_data, derivation_rules, formal_constraints, blueprint |
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-shot nearest fix): use repair_path to explain or audit the fix, or compare alternative r Inputs: api_key, structured_data, blueprint, max_depth, rank_by |
rotate_api_key | Replace an API key with a fresh one. The old key stops working immediately; the new key inherits its bindings. Inputs: api_key, key_to_rotate |
structural_types | Retrieve the document categories a discover_patterns session identified (counts, distinguishing fields, domain hints). Read-only; returns status=no_session if discovery has not run for this namespace. Inputs: api_key, blueprint |
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 accumulated repairs. Inputs: api_key, chain_id, stage, structured_data |
update_blueprint | Update an existing Blueprint in place. Only passed fields change; pass [] to clear a list. workflow_name cannot be renamed and existing API keys keep working. Different from create_blueprint: modifies an existing Blueprint, mints no new key Inputs: api_key, workflow_name, customer_name, mode, extracted_fields, derived_fields |
validate | Validate structured data against a Blueprint's rules BEFORE the result is used. Returns PASS, FAIL, or REVIEW with plain-language findings, repair suggestions, a determinism hash, and a re-verifiable certificate. Same input + same rules = s Inputs: api_key, structured_data, blueprint |
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 same call. Same verdicts as validate: PASS, FAIL, or REVIEW, with reasons and proof. Inputs: api_key, structured_data, blueprint |
verify_certificate | Independently re-verify a validation certificate. Integrity mode checks the hash chain; full mode (certificate + original data) recomputes every attested rule from scratch - trust nothing, recheck everything. Inputs: api_key, certificate, data, derivation_rules |
verify_replay | Verify two replay contracts represent the same deterministic execution: same input + same rules = same result, byte-identical. Mismatch fields localize the cause (data, rules, platform version, or trace). Use to prove a past decision reprod Inputs: api_key, contract_a, contract_b |
Every block below points at https://app.geodesiclabs.ai/mcp. Pick your client and copy.
claude mcp add --transport http governance-platform https://app.geodesiclabs.ai/mcp
{
"mcpServers": {
"governance-platform": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://app.geodesiclabs.ai/mcp"]
}
}
}{
"mcpServers": {
"governance-platform": {
"url": "https://app.geodesiclabs.ai/mcp"
}
}
}{
"servers": {
"governance-platform": {
"type": "http",
"url": "https://app.geodesiclabs.ai/mcp"
}
}
}{
"context_servers": {
"governance-platform": {
"url": "https://app.geodesiclabs.ai/mcp"
}
}
}{
"mcpServers": {
"governance-platform": {
"serverUrl": "https://app.geodesiclabs.ai/mcp"
}
}
}{
"mcpServers": {
"governance-platform": {
"url": "https://app.geodesiclabs.ai/mcp"
}
}
}name: Governance Platform
version: 0.0.1
schema: v1
mcpServers:
- name: Governance Platform
type: streamable-http
url: https://app.geodesiclabs.ai/mcp{
"mcpServers": {
"governance-platform": {
"httpUrl": "https://app.geodesiclabs.ai/mcp"
}
}
}{
"mcpServers": {
"governance-platform": {
"type": "http",
"url": "https://app.geodesiclabs.ai/mcp"
}
}
}{
"mcpServers": {
"governance-platform": {
"url": "https://app.geodesiclabs.ai/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fapp.geodesiclabs.ai%2Fmcp&type=streamable_http&id=governance-platform&name=Governance%20Platform
It answered our last check on 17 October 2026 in 425 ms. Over 10 checks since 4 September 2026 it answered 10. Status here comes from Neuronto's own probes, not from the publisher.
Yes. It is published by geodesiclabs.ai and served from app.geodesiclabs.ai, the vendor's own domain: https://app.geodesiclabs.ai/mcp.
37, as returned by the server's own tools/list on 7 September 2026: account_status, analyze_anomaly, approve_rule, authorize_execution, check_blueprint_health, check_drift, check_realization, compare_semantic_equivalence, and 29 more.
It answered our last check on 17 October 2026 in 425 ms. Over 10 checks since 4 September 2026 it answered 10.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://app.geodesiclabs.ai/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: ai.geodesiclabs. Endpoint host: app.geodesiclabs.ai. ARD identifier: urn:air:ai.geodesiclabs:mcp:governance-platform.
First indexed 31 August 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.