MudraID - 2026 Pricing, Features, Reviews & Alternatives

MudraID is cloud-based identity and trust infrastructure built for organizations deploying autonomous AI agents in production. It assigns every agent a verifiable cryptographic identity, enables principals to delegate scoped, time-bound, and revocable authority, and evaluates every agent request against current policy, trust state, and revocation status at the exact moment the action is attempted. Evidence-based trust scoring, write-once governance policy, and an append-only, hash-chained audit trail are included without requiring architectural changes to existing environments. MudraID integrates with existing identity providers (Entra, Okta, Auth0, and any OIDC/JWKS-compatible provider) and SIEM tooling, and works across modern and legacy environments including static sites, API platforms, MCP (Model Context Protocol) tool calls, and existing API gateways via a Kong-first gateway enforcement model with a portable adapter contract.

MudraID targets platform and product teams that expose agent-accessible APIs covering refunds, payments, and admin actions, as well as security and IAM teams that require verifiable control and audit evidence over AI agent behavior. It is aligned with the IETF AIMS framework and the AI agent identity model, uses WIMSE/SPIFFE-compatible agent identifiers, and delegates authority via OAuth 2.0, positioning it on open standards rather than proprietary infrastructure. Agent-to-agent delegation chains are supported, and compromised authority can be quarantined and revoked with delegation cascade from a single point of control.

The platform captures every action outcome as tenant-safe, versioned, and independently verifiable proof for auditors and reviewers. Automated key rotation, a Python Agent SDK, and MCP tool and API action mapping reduce integration overhead for engineering teams. No CAPTCHAs are introduced, false positives are reduced, and accountability is maintained at the per-request level, giving both security and product teams clear, evidence-backed records of every consequential agent action taken in production.