Backend Architect MCP Server
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| initialize_projectB | Creates the folder structure and pyproject.toml configured for uv. Defaults to current directory. |
| save_organization_contextC | Saves the organizational context and complex operation requirements to state. |
| save_roles_planC | Saves user roles/permissions to state. Each role should have 'name', 'description', and 'permissions'. |
| save_database_planC | Saves table schemas (fields, types, relationships) to state. |
| save_route_planB | Saves API endpoints (method, path, summary) to state. |
| save_test_planC | Saves simulation scenarios to state. |
| get_next_pending_taskA | Returns the first unbuilt item. Priority: Models -> Routes -> Tests. |
| get_file_instructionC | Returns a strict SYSTEM PROMPT for the agent to write the code. |
| write_component_fileC | Writes the file and marks the task as done. |
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 9 tools
Each tool has a clearly distinct purpose with no overlap: get_file_instruction provides a prompt, get_next_pending_task fetches tasks, initialize_project sets up structure, save_* tools store different planning aspects, and write_component_file writes files. The descriptions clearly differentiate their functions, preventing agent misselection.
The naming follows a consistent verb_noun pattern with minor deviations: most tools use verb_noun (e.g., save_database_plan, initialize_project), but get_file_instruction and get_next_pending_task use verb_adjective_noun, and write_component_file uses verb_noun_noun. This slight inconsistency is readable but not perfectly uniform.
With 9 tools, the count is well-scoped for backend project management, covering initialization, planning, task management, and file writing. Each tool earns its place by addressing specific aspects of the workflow, avoiding bloat or thin coverage.
The tool set covers core backend development workflows: project setup, planning (database, roles, routes, tests, context), task management, and file writing. Minor gaps exist, such as no tools for updating or deleting plans, but agents can work around this by re-saving or using existing tools effectively.