Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@erm-github-mcp Ping the server and show its server info"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A barebones Model Context Protocol (MCP) server written in TypeScript. Designed to be built from source, containerized with Docker, and deployed to IBM Code Engine.
Related MCP server: My Awesome MCP
This server supports two transports:
Transport | When it's used | How to activate |
stdio | Local development / Bob desktop | Default (no env var needed) |
HTTP Streamable | Docker / Code Engine |
|
The HTTP transport exposes a /health endpoint at GET /health for liveness probes.
.
├── src/
│ └── index.ts # Server entry point — add tools here
├── build/ # Compiled output (git-ignored)
├── .github/
│ └── workflows/
│ └── build-push.yml # CI: typecheck → build → push to GHCR
├── Dockerfile # Multi-stage build (builder + runtime)
├── docker-compose.yml # Local container testing
├── tsconfig.json
└── package.jsonTool | Description |
| Health-check — returns |
| Returns server name, version, transport, Node version, and uptime |
Node.js 20+
npm 10+
npm install
npm run buildnode build/index.jsMCP_TRANSPORT=http PORT=3000 node build/index.jsTest the health endpoint:
curl http://localhost:3000/healthdocker build -t erm-github-mcp .docker run -p 3000:3000 erm-github-mcpdocker compose up --buildThe workflow at .github/workflows/build-push.yml runs on every push to main and on version tags (v*):
TypeScript build — npm ci + tsc (fails fast on type errors)
Docker build & push — multi-platform image (linux/amd64, linux/arm64) pushed to the GitHub Container Registry (GHCR)
The image is published as:
ghcr.io/<your-github-username>/erm-github-mcp:<tag>No secrets need to be configured — the workflow uses the built-in GITHUB_TOKEN.
After the first push, go to GitHub → Packages → erm-github-mcp → Package settings and set visibility to Public so Code Engine can pull it without credentials.
IBM Cloud CLI with the Code Engine plugin:
ibmcloud plugin install code-engineAn IBM Cloud account and a Code Engine project
ibmcloud ce project select --name <your-project-name>Replace <tag> with the image tag you want to deploy (e.g. main or v0.1.0):
ibmcloud ce application create \
--name erm-github-mcp \
--image ghcr.io/<your-github-username>/erm-github-mcp:<tag> \
--port 3000 \
--min-scale 0 \
--max-scale 5 \
--env MCP_TRANSPORT=http \
--env PORT=3000ibmcloud ce application get --name erm-github-mcp --output urlibmcloud ce application update \
--name erm-github-mcp \
--image ghcr.io/<your-github-username>/erm-github-mcp:<new-tag>Variable | Default | Description |
|
| Set to |
|
| HTTP port the server listens on |
Add the following to your Bob mcp.json:
{
"mcpServers": {
"erm-github-mcp": {
"url": "https://<your-code-engine-url>"
}
}
}{
"mcpServers": {
"erm-github-mcp": {
"command": "node",
"args": ["/absolute/path/to/erm-github-mcp/build/index.js"]
}
}
}Add new tools in src/index.ts using server.tool():
server.tool(
"my_tool",
"Description shown to the AI",
{
input_field: z.string().describe("What this field does"),
},
async ({ input_field }) => ({
content: [{ type: "text", text: `Result: ${input_field}` }],
})
);Then rebuild:
npm run buildReturns metadata about this running MCP server instance.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Returns metadata' implies a read-only operation, but it does not explicitly say so, nor does it disclose what the response contains or whether there are side effects. For a zero-parameter tool this is adequate, but it misses the chance to confirm non-mutating behavior and response shape.
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?
A single, front-loaded sentence with no wasted words. It states the verb, resource, and scope efficiently. Perfect for a zero-parameter tool.
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?
For a simple read-only metadata tool with no parameters and no output schema, the description is mostly complete. It tells the agent what the tool does. However, it could be slightly more explicit about the types of metadata returned (e.g., server version, protocol, capabilities) and could mention that it is safe to call without side effects. The lack of any relationship to 'ping' also leaves a small gap.
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 there is nothing for the description to explain beyond what the schema already shows (empty properties). The baseline is 4 because the schema fully covers parameters, and the description adds no ambiguity. No extra value needed.
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 states a clear verb ('Returns') and resource ('metadata about this running MCP server instance'). It distinguishes from ping (which implies liveness check), though 'metadata' is generic and could be more specific about what metadata (e.g., version, capabilities). Still, the purpose is unmistakable.
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?
No guidance on when to use this vs the sibling tool 'ping'. Both relate to server status, but the description doesn't explain which to call for what. An agent would have to infer that ping checks connectivity while this fetches metadata, but no explicit when/when-not is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Health-check tool. Returns 'pong' and echoes the optional message back.
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | Optional message to echo back |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden, and it discloses both the return value ('pong') and the side effect (echoing the message). 'Health-check' strongly implies a non-mutating, safe operation. It does not explicitly state non-destructiveness, but for a ping the disclosed behavior is effectively complete.
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?
Two short sentences, no filler, with the purpose front-loaded before the return-behavior detail. Every word earns its place; this is a model of concise health-check documentation.
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?
For a tool this simple — one optional parameter, no required fields, no nested objects, no output schema — the description tells an agent everything needed to call it correctly and predict the response. Nothing meaningful is missing.
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?
Schema coverage is 100%, so the single message parameter is already documented ('Optional message to echo back'). The description reinforces the echo behavior in prose, which adds marginal context beyond the schema but does not materially expand on it, landing at the baseline for high-coverage schemas.
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 states a specific purpose ('health-check tool') and the precise behavior ('returns pong and echoes the optional message back'). This is clear, specific, and inherently distinguishes it from the get_server_info sibling, whose name implies returning server details rather than a liveness signal.
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 'health-check tool' phrasing implies when it should be used, and it is self-evident for a ping utility. However, there is no explicit guidance on when to prefer this over get_server_info or any stated exclusions. For a trivial tool the context is clear enough, but it stops short of explicit alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0get_server_infopingThe two tools serve clearly distinct purposes: ping is a health check, while get_server_info provides instance metadata. There is zero overlap between them.
Both tools follow a consistent verb_noun naming pattern (ping, get_server_info) with snake_case, matching the expected convention.
With only two generic tools and a server name indicating GitHub integration, the count is severely inadequate. The tools are trivial and unrelated to the apparent domain, representing an extreme mismatch.
The server name implies GitHub functionality, but the tool surface offers only health check and server info. No GitHub operations exist, leaving obvious and critical gaps.
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If you are the server author, to access and configure the admin panel.
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