by Inflectra
Enables AI assistants to perform operations in Inflectra Spira platforms—SpiraTest, SpiraTeam, and SpiraPlan—by translating natural‑language requests into Spira REST API calls.
Spira MCP Server is a Model Context Protocol (MCP) service that bridges conversational AI (e.g., Claude) and the Inflectra Spira suite. It exposes a set of MCP tools that map natural‑language intents to the Spira REST API, allowing AI assistants to retrieve, create, and update artifacts across SpiraTest, SpiraTeam, and SpiraPlan.
git clone https://github.com/Inflectra/mcp-server-spira.git
cd mcp-server-spira
pip install -e .
.env
file in the project root:
INFLECTRA_SPIRA_BASE_URL=https://mycompany.spiraservice.net
INFLECTRA_SPIRA_USERNAME=your_login
INFLECTRA_SPIRA_API_KEY=YOUR_API_KEY
mcp dev src/mcp_server_spira/server.py
or in production mode:
python -m mcp_server_spira
requirements.md
, design.md
, tasks.md
, test-cases.md
) for AI‑driven development tools.Q: Which Spira editions are supported? A: All three editions – SpiraTest, SpiraTeam, and SpiraPlan.
Q: Do I need to write code to call the MCP tools? A: No. Once the server is running and configured, any MCP‑compatible assistant can invoke the tools via natural language.
Q: How is authentication handled?
A: By providing INFLECTRA_SPIRA_USERNAME
and INFLECTRA_SPIRA_API_KEY
in the .env
file; the server uses these credentials for all REST calls.
Q: Can I run the server inside Docker?
A: Yes. Install the package in a Docker image, copy the .env
file, and start the server with python -m mcp_server_spira
.
Q: How do I add new MCP tools?
A: Extend the features/
modules with additional functions following the existing pattern and register them in the server entry point.
A Model Context Protocol (MCP) server enabling AI assistants to interact with Spira by Inflectra.
This project implements a Model Context Protocol (MCP) server that allows AI assistants (like Claude) to interact with the Inflectra Spira platform, providing a bridge between natural language interactions and the Spira REST API.
This server supports all three editions of Spira:
The Spira MCP server current implements the following features:
This feature provides easy access to the list of artifacts that have been assigned to the current user
This feature provides tools that let you retrieve and modify the different workspaces inside Spira
This feature provides tools that let you retrieve and modify the different artifacts inside a Spira program
This feature provides tools that let you retrieve and modify the different artifacts inside a Spira product
This feature provides tools that let you view and modify the configuration and settings of Spira product templates
This feature provides tools that let you integrate automated DevOps tools such as test automation frameworks and CI/CD pipelines
Provides operations for retrieving the product specification files that can be used to build the functionality of the product using AI. This is used by Agentic AI development tools such as Amazon Kiro for building applications from a formal spec.
This module provides the following MCP tools for retrieving the entire product specifications:
requirements.md
filedesign.md
filetasks.md
filetest-cases.md
file# Clone the repository
git clone https://github.com/Inflectra/mcp-server-spira.git
cd mcp-server-spira
# Simple development mode install
pip install -e .
# Install into a virtual development environment (you may need to create one with uv venv)
uv pip install -e ".[dev]"
# Install from PyPi
pip install mcp-server-spira
Create a .env
file in the project root with the following variables:
INFLECTRA_SPIRA_BASE_URL=The base URL for your instance of Spira (typically https://mycompany.spiraservice.net or https://demo-xx.spiraservice.net/mycompany)
INFLECTRA_SPIRA_USERNAME=The login name you use to access Spira
INFLECTRA_SPIRA_API_KEY=The API Key (RSS Token) you use to access the Spira REST API
Note: Make sure your API Key is active and saved in your Spira user profile.
# Development mode with the MCP Inspector
mcp dev src/mcp_server_spira/server.py
# Production mode using shell / command line
python -m mcp_server_spira
# Install in Claude Desktop
mcp install src/mcp_server_spira/server.py --name "Inflectra Spira Server"
To run the MCP server from within Cline, you don't use the commands above, instead you add the Inflectra MCP server to the configuration JSON file cline_mcp_settings.json
:
{
"mcpServers": {
"inflectra-spira": {
"autoApprove": [
"get_my_incidents",
"get_products",
"get_test_cases"
],
"timeout": 60,
"command": "uv",
"args": [
"--directory",
"C:\\Git\\mcp-server-spira",
"run",
"main.py"
],
"env": {
"INFLECTRA_SPIRA_BASE_URL": "https://mycompany.spiraservice.net",
"INFLECTRA_SPIRA_USERNAME": "login",
"INFLECTRA_SPIRA_API_KEY": "{XXXXXX-XXXXXXX-XXXXXXX-XXXXXXX-XXXXX}"
},
"type": "stdio"
}
}
}
To run the MCP server from within Kiro, you don't use the commands above, instead you add the Inflectra MCP server to the configuration JSON file mcp.json
:
{
"mcpServers": {
"inflectra-spira": {
"command": "uv",
"args": [
"--directory",
"C:\\Git\\mcp-server-spira",
"run",
"main.py"
],
"env": {
"INFLECTRA_SPIRA_BASE_URL": "https://myinstance.spiraservice.net",
"INFLECTRA_SPIRA_USERNAME": "mylogin",
"INFLECTRA_SPIRA_API_KEY": "{XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXX}"
},
"disabled": false,
"autoApprove": [
"get_specification_requirements",
"get_specification_design",
"get_specification_tasks",
"get_specification_test_cases"
]
}
}
}
Get me my assigned tasks in Spira/
Get me my assigned requirements in Spira/
List all projects in my organization and show me the iterations for the Development team
The project is structured into feature modules, each implementing specific Inflectra Spira capabilities:
features/mywork
: Accessing a user's assigned artifacts and updating their status/progressfeatures/projects
: Project management capabilitiesfeatures/programs
: Program management featuresutils
: Common utilities and client initializationFor more information on development, see the CLAUDE.md file.
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
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