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Runtime permission, approval, and audit layer for AI agent tool execution.
Runtime permission, approval, and audit layer for AI agent tool execution.
Remote endpoints: streamable-http: https://api.oakallow.io/mcp
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-oakallow-oakallow": {
"url": "https://api.oakallow.io/mcp"
}
}
}From the project's GitHub README.
Runtime permission, approval, and audit governance for AI agent tool execution.
Oakallow is a hosted remote MCP server. It sits between an agent and the actions it wants to take, so that a specific action can be checked, gated behind human approval when it is risky, authorized with a single-use signed token, and recorded in an immutable audit log, at the moment of execution.
https://api.oakallow.io/mcp (Streamable HTTP)Oakallow injects a governance checkpoint into a workflow that may also use other connectors. An agent does its investigative work (for example, looking up an account through another connector), forms a recommendation, and calls Oakallow to request approval for the action. A human approver then decides in the Oakallow dashboard or mobile app, under enforced multi-factor authentication.
The connector is a requester and pass-through, not a decider:
| Tool | Purpose | Reads only |
|---|---|---|
list_my_tools | Enumerate the tools available to the signed-in user in the named org (org arg; see below) | yes |
check_permission | Ask whether a given tool call would be allowed, require approval, or be blocked (takes an org arg; see below) | yes* |
list_pending_approvals | List approval requests still awaiting a human decision | yes |
check_approval_status | Poll a pending approval request by reference number | yes |
* check_permission returns a read-only verdict only — it does NOT create an approval or
a reference. (The approval and its REF-… are created when you call the gated tool itself
through oakallow.) It does have one side effect by design: checking an unregistered tool
makes Oakallow auto-create a gated draft entry for it (with conservative, fail-closed
defaults) so the eventual call is governed and the owner can triage it from the dashboard.
This is intentional: an unknown tool is never silently trusted.
An Oakallow account can have more than one organization, and each org sets its own tools, permission rules, approvers, and alert paths. So an action must be checked against the right org — that is what determines who gets asked to approve and under which rules.
check_permission and list_my_tools accept an optional org argument: the org's
external id (e.g. org_oak_…). The rule:
org. The connector uses your only org.org naming the org the action targets. If you omit it, the
call is refused with guidance rather than guessing the wrong org.You don't ask the connector to list your orgs — there is no org-enumeration tool. Instead,
download the org-specific skill from that org's dashboard. Each org's skill carries its
own org id and tells the agent to pass it. Install one skill per org you operate in; the
agent reads the matching skill and passes the right org on every call.
The connector authorizes the org you pass against your signed-in identity: you can only
target an org you can actually act in (you are its team owner/admin, or you are in that
org's approver group). Passing an org you don't have access to is refused — the skill is a
convenience, not a grant of access.
oakallow exposes two read-only MCP resources. They are preflight signals an agent (or a
client UI) can read before committing to route an action through oakallow. Both require
the mcp:read scope, neither is a tool call, and neither is billed.
| Resource | Returns | Reads only |
|---|---|---|
oakallow://status | Liveness of the connector for the signed-in session: status, endpoint, server version, protocol version, and the granted scopes. A successful read is itself the proof the session is valid. No account identity or PII is returned. | yes |
oakallow://credits | Whether a governed call would currently be funded for the org this session resolves to, so an agent can fail fast before requesting an approval that could not be paid for. | yes |
oakallow://credits is scoped to the caller's own billing org and resolves it the same
way a real tool call does, so a can_fund: true result genuinely means the eventual
approval will be funded (including team-pool fallback). It returns only a can_fund
boolean and the org's name and external id. It deliberately discloses no balance figures:
dollar amounts are surfaced only to the team owner in the dashboard, never over the
connector. If the session resolves to no org, or to more than one, it returns
can_fund: false with a reason rather than guessing which org would be billed.
The remote endpoint requires OAuth 2.1 (PKCE) — there is no anonymous access. An oakallow account is the prerequisite for connecting.
Add https://api.oakallow.io/mcp as a custom connector in your MCP client (Claude,
Claude Desktop, Cowork, ChatGPT, or any Streamable HTTP MCP host). You will be redirected
to sign in to Oakallow and approve the requested scopes:
mcp:read: list tools, view pending approvals, check permissions, read activity.mcp:write: create approval requests and mint run tokens.You don't configure any of this by hand: an unauthenticated request returns 401 with a
WWW-Authenticate header pointing to the endpoint's RFC 9728 protected-resource metadata
(/.well-known/oauth-protected-resource), so a spec-compliant MCP client discovers the
authorization server and runs the OAuth flow automatically.
See examples/ for a Claude Desktop config and an OAuth flow walkthrough.
SKILL.md is an agent skill that documents when and how to use the
oakallow tools: the request, approve, poll, and act workflow, how to phrase
approval reasons, and what to do on allowed, requires_approval, or blocked
verdicts. Point your agent at it to govern tool actions correctly.
PROMPT.md has short, copy-paste one-liners to drop into your
agent's system prompt so it actually consults the skill. The skill is the
procedure; a trigger prompt is what makes the agent look. Three options, from
"gate every tool call" to "gate a customer-named set," plus an inline example
pattern for a real request.
Oakallow lives outside the execution path. It governs and records what was reported; it does not run your tools or receive your tool parameters beyond a PII-scrubbed reason.
See LICENSE.
See CHANGELOG.md.
© Islemonics Studios LLC. Patent pending.
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