Intended to integrate with Welcome to the Jungle recruitment workflows, providing read-only access to organization, job, candidate, and movement data. Note: the integration is not implemented yet.
Click on "Deploy 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., "@JungleBridge MCP What's your connection status?"
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.
Your Welcome to the Jungle recruitment workflows, in your AI assistant.
Development scaffold — the WTTJ integration is not implemented yet.
This repository provides a working local FastMCP STDIO server and a reproducible
Python development environment. Its only tool, get_connection_status, returns
not_implemented; it makes no API request and reads no credentials.
Open this repository in VS Code and choose Dev Containers: Reopen in Container.
Python, uv and Claude Code are included. Run claude inside the container to sign in.
Or install uv locally:
make bootstrap
make check
make audit
make build
uv run --no-sync junglebridge-mcpThe last command waits for a client speaking MCP over STDIO; it is not a chat CLI. See the French development guide, architecture, capability matrix and security notes.
Related MCP server: MCP Server Template
Read-only organization, job, candidate and movement tools, then bounded recruitment summaries. API access and scopes must be confirmed before a private pilot. No automated candidate ranking, hiring decisions, emails or job publication. No affiliation or partnership with Welcome to the Jungle is claimed.
Apache-2.0. Community is independent and intended for self-managed professional use. Optional proprietary enterprise extensions will live in a separate repository. No commercial Community quota is planned; upstream and technical limits will apply.
Return scaffold status only; does not verify or contact the WTTJ API.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| detail | No | |
| status | No | |
| api_verified | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses the critical behavioral trait that this tool never contacts the external API. This is essential context an agent needs to interpret the returned status correctly and to avoid assuming a live connection test.
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, front-loaded sentence with no filler. Every word earns its place: it states what is returned and explicitly rules out a major misconception.
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?
With an output schema available, the description only needs to clarify the tool's semantic scope, which it does. The negative statement about the API prevents a likely misinterpretation, and combined with the annotations, the definition is fully sufficient for an agent to call it correctly.
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 to document. Per the baseline rule for 0-parameter tools, the description needn't explain parameter behavior, and the existing sentence contains all necessary information.
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 identifies a specific verb ('Return') and resource ('scaffold status'), and explicitly states what it does not do ('does not verify or contact the WTTJ API'). This makes the tool's exact function unmistakable even without siblings.
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 negative clause 'does not verify or contact the WTTJ API' communicates an important usage boundary: this is not a live connectivity check. It doesn't name explicit alternatives, but with no sibling tools and a zero-parameter scope, it provides clear context for when to call it.
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.
v0.1.0get_connection_statusScored across 1 tool
With only a single tool, there is no possibility of confusion or overlap. The tool's purpose is clearly stated, albeit limited.
The single tool follows the snake_case verb_noun pattern (get_connection_status), which is consistent and predictable.
A server with only one trivial tool that merely returns a scaffold status without any real API interaction is an extreme mismatch for the apparent purpose of a JungleBridge MCP. It feels like a placeholder rather than a functional server.
The tool does not actually verify or contact the WTTJ API, and there are no other tools to cover any meaningful operations. The surface is severely incomplete and would cause agent failures.
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