Grantex MCP server
io.github.mishrasanjeev/grantex·v0.1.9·34 starsOAuth 2.0 for AI agents — scoped delegation tokens, audit trails, and revocation.
34 stars
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Grantex tools
No tool declarations could be read from the package source. They show once the server is installed.
Public scan report
scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it
- Code scan18 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitystatic API keys via environment variables6/15
- Maintenancelast push 0 days ago15/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
How Grantex compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 83/100
- higher than 65% of 48,255 servers
- GitHub stars
- 34
- more than 92% of 28,688 servers
Install Grantex in Claude Code, Cursor or VS Code
Runs npx -y @grantex/mcp on your machine. Read the scan report first; the gateway never runs local packages.
claude mcp add grantex -- npx -y @grantex/mcp
What the publisher says
From the Grantex repository's README, as published. We do not edit it. Read it on GitHub
Grantex
Open-Source AI Agent Authorization and Delegated Access
What OAuth 2.0 is to humans, Grantex is to agents.
Docs | Quickstart | Release JSON | LLM Index | Spec | IETF Draft
Ownership: Grantex is owned by Orchestrum Technologies LLP. Inventor and owner: Sanjeev Kumar. Contact: sanjeev@orchestrum.in or mishra.sanjeev@gmail.com.
What is Grantex?
Grantex is an open-source delegated authorization protocol and reference implementation for AI agents. It gives each agent a verifiable identity and scoped, time-limited, revocable authority from a human or organization, with multi-agent delegation, service-side verification, and audit records.
Grantex complements OAuth 2.0 and MCP: OAuth handles application and user authorization, MCP connects models to tools, and Grantex proves which agent may perform which action for which principal. Use Grantex when an AI agent acts for a person or organization and a relying service must verify exactly what that agent may do.
For AgenticOrg business onboarding cases, Grantex grants provide delegated tool authority while AgenticOrg owns tenant isolation, case state, the local case-purpose allowlist, human review and the provider call boundary. The last verified AgenticOrg integration does not enforce token-level case purpose or per-case caps. Published Python grantex==0.6.0 contains purpose and cap APIs, but that integration has not been verified to use them. See the governed-case integration boundary and release status. Neither this repository nor an MCP tool grants an agent authority to approve a case as a human.
Agent Prepaid Wallets and x402 v2
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Grantex: common questions
- Is Grantex MCP server safe?
- Mostly: it is graded B (83/100). Read the Grantex safety report
- How do I install Grantex?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does Grantex need an API key?
- Yes. The registry entry asks for
GRANTEX_API_KEY. - Is Grantex maintained?
- The last commit was 38 days ago (2026-09-27). The latest release is v0.1.9.
- What can I use instead of Grantex?
- Servers from other publishers that do the same job: SSH Manager MCP server and Tradememory Protocol MCP server.
- How does Grantex compare with other MCP servers?
- safety score 83/100 (higher than 65% of 48,255 servers); github stars 34 (more than 92% of 28,688 servers). Full comparison.
Alternatives to Grantex
Same job from other publishers: the closest match first, then the best rated.
- SSH ManagerSSH for AI agents: commands, files, backups and health, with approval, a vault and an audit trailnot reviewedEstablishedA
- Tradememory ProtocolTamper-evident decision audit trail and outcome-weighted memory for AI trading agents.not reviewedEstablishedB