gh_list_orgsList organizations you're a member of. Returns org names, URLs, and your role (owner, member, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of items returned. | |
| items | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Number of items returned.",
+ "type": "integer"
+ },
+ "items": {
+ "items": {
+ "properties": {
+ "avatar_url": {
+ "description": "Organization avatar URL",
+ "type": "string"
+ },
+ "description": {
+ "description": "Organization description",
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "html_url": {
+ "description": "Organization web URL",
+ "type": "string"
+ },
+ "id": {
+ "description": "Organization ID",
+ "type": "number"
+ },
+ "login": {
+ "description": "Organization login",
+ "type": "string"
+ },
+ "url": {
+ "description": "Organization API URL",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "items",
+ "count"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {}
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, non-destructive behavior. The description adds value by disclosing the return payload fields (org names, URLs, role), which is beyond the annotations. It also implies the scope is restricted to the authenticated user's memberships, adding behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that front-loads the primary action ('List organizations you're a member of') and then specifies return values. No wasted words, perfectly concise for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, a rich output schema, and strong annotations, the description is fully complete. It states what is listed and what fields are returned. There are no gaps in prerequisites, side effects, or complex behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema provides no semantics to clarify. Baseline for 0 params is 4; the description does not need to compensate. It adds no parameter-related details, but none are required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists organizations the user is a member of, with a specific verb ('List') and resource ('organizations'). It distinguishes from siblings like gh_list_repos and gh_list_issues by the object type. The added detail about returning org names, URLs, and roles sharpens the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool—when you need your GitHub organizations—but does not explicitly state alternatives or exclusion criteria. No mention of when not to use it or more specialized alternatives. It is a simple, self-evident tool, but lacks explicit guidance compared to the 'get_calls' example.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
There is significant overlap among many tools: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all serve query-answer purposes with subtle differences, and multiple polymarket tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) cover similar arbitrage/mispricing territory. Additionally, ai_visibility_check and scan_competitor_ai_presence clearly overlap, making it hard to pick the right one.
Tool names follow no consistent pattern. Some use a gh_ prefix (gh_get_file, gh_get_repo, etc.), others are descriptive phrases (ask_pipeworx, compare_entities, bet_research), and a few are plain verbs (remember, recall, forget, subscribe, unsubscribe). The mixed conventions and varied verb/noun styles make the set feel disjointed.
At 37 tools, the count is high but still within a usable range. However, the server is named 'Github_private' yet includes only 7 GitHub-specific tools and 30+ unrelated tools (Pipeworx data, Polymarket betting, memory, etc.). This suggests the server aggregates multiple unrelated domains, making the count feel bloated for its apparent GitHub purpose.
Given the server name, the GitHub tool surface is severely incomplete: there are no create/update/delete operations for repos, no PR creation or merging, no issue comments, no branches, and no search across repos. The Pipeworx side is fairly comprehensive, but the mismatch between the server name and the actual tool set leaves major gaps for expected GitHub workflows.