Jinni: Bring Your Project Into Context
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| usageA | Retrieves the Jinni usage documentation (content of README.md). |
| read_contextA | Reads context from a specified project root directory (absolute path). Focuses on the specified target files/directories within that root. Returns a static view of files with paths relative to the project root. Assume the user wants to read in context for the whole project unless otherwise specified - do not ask the user for clarification if just asked to read context. If the user just says 'jinni', interpret that as read_context. If the user asks to list context, use the list_only argument. Both Guidance for AI Model Usage When requesting context using this tool:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have completely distinct purposes: 'read_context' is for reading project files and directories, while 'usage' is for retrieving documentation. There is no overlap or ambiguity between them; an agent would never confuse one for the other.
Both tools use snake_case naming, which is consistent. However, 'read_context' follows a verb_noun pattern, while 'usage' is a noun only, representing a minor deviation from a fully uniform convention.
With only 2 tools, the server feels thin for its purpose of bringing projects into context. While 'read_context' is core, there are likely missing operations like updating context, managing rules, or querying context metadata, making the set under-scoped.
The tool surface is severely incomplete for the domain of project context management. It only supports reading context and accessing documentation, lacking essential operations such as writing/modifying context, listing available contexts, or configuring rules beyond defaults, which will limit agent capabilities.