OrionBI

Get a GitHub issue

github_get_issue

Read-only

Get a single issue (title, body, state, labels, author) from a repository you can access with a GitHub connection (your own or one shared with you).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "repo": "<repo>",
      "number": "<number>"
    },
    "name": "github_get_issue"
  }
}

Input Schema

Name	Required	Description
`repo`	Yes	Repository in "owner/repo" form, e.g. octocat/Hello-World. The owner is the GitHub LOGIN exactly as it appears in the repository URL (github.com/<owner>/<repo>) — not a display name, and not the connection's name.
`number`	Yes	Issue number.
`connection`	No	Which GitHub connection to use, by its name from github_list_connections. This is a local label for the connection, NOT a GitHub username — for anything GitHub has to resolve, use that connection's login instead. Optional when you have exactly one.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 4, 2026

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered; the description still adds real context by scoping credentials (own or shared connection) and naming the fields returned. It omits behavioral caveats such as GitHub returning pull-request-backed entries from the issues endpoint and 404/not-found behavior, which keeps it short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One front-loaded sentence with no filler: the action, the returned payload, and the access condition, in that order. Nothing is redundant with the title or restated.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple three-parameter read tool with a fully documented schema, the description supplies the essential missing piece — a summary of the return payload — in lieu of an output schema. It stops short of noting error cases or that the issues endpoint can return pull requests, which an agent would benefit from knowing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% — repo format, owner-login semantics, issue number, and the connection-label distinction are all fully documented in the schema. The description adds nothing about parameters beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Get a single issue") and enumerates the returned fields (title, body, state, labels, author), which cleanly separates it from list-style siblings like github_list_issues. It does not explicitly name those siblings, so differentiation is implied by "single" rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The access constraint ("from a repository you can access with a GitHub connection — your own or one shared with you") implies when the call is viable, but there is no explicit when-to-use/when-not guidance and no routing to github_list_issues or github_search_code for the lookup case. Usage is inferable rather than directed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All OrionBI tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?