langchain-taiga 2.8.0

Python toolkit that lets your LangChain agents automate Taiga: create, search, edit & comment on user stories, tasks and issues via the official REST API. v2 introduces the multi-tenant remote MCP mode (HTTP+OAuth) alongside the existing stdio transport. v2.5+ adds OAuth refresh-token rotation, attachment read/write tools (list/get/inline-base64 upload), and dropdown-choice discovery on list_custom_attributes_tool.

langchain-taiga

Taiga integration for LangChain and the Model Context Protocol.

The package ships three things in one install:

1. 21 LangChain tools for Taiga (entities, wiki, custom attributes, members, sprint planning).
2. A TaigaToolkit that bundles them for one-line LangChain agent setup.
3. An MCP server in two flavours:
   • Stdio mode — single-user, local credentials in env vars. For Claude Desktop, Claude Code, VSCode local.
   • Remote mode — multi-tenant HTTP server with OAuth 2.1 + PKCE + Dynamic Client Registration. For claude.ai Custom Connectors, VSCode Web, Claude Desktop with HTTP transport, etc. Each user signs in with their own Taiga credentials; the server stores no static API key.

The 21 tools:

• create_entity_tool: Creates user stories, tasks and issues in Taiga.
• search_entities_tool: Searches for user stories, tasks and issues in Taiga. Returns {matches, count, max_results, truncated}. Supports max_results and include_custom_attributes (default False — opt-in to avoid an N+1 fetch storm). Date filters are tz-aware.
• get_entity_by_ref_tool: Gets a user story, task or issue by reference. For user stories, the response also includes a points field ({role_name: value} shape, symmetric to set_userstory_points_tool's input) so a read + write round-trip stays in the same vocabulary.
• update_entity_by_ref_tool: Updates a user story, task or issue by reference.
• add_comment_by_ref_tool: Adds a comment to a user story, task or issue.
• add_attachment_by_ref_tool: Adds an attachment to a user story, task or issue by downloading a public URL (the server fetches it via requests.get).
• add_attachment_inline_by_ref_tool: Uploads a local file as an attachment by inlining its bytes as base64. Symmetric to get_attachment_by_ref_tool. Use when the file lives on the calling client (Claude Code, claude.ai) and shouldn't be exposed via a public URL. Refuses payloads whose decoded size exceeds TAIGA_MAX_INLINE_ATTACHMENT_BYTES (default 10 MB).
• list_attachments_by_ref_tool: List all attachments on an entity with fresh signed download URLs. URL tokens from the Taiga UI/webhook diff expire after ~6 min; this tool re-mints them on every call.
• get_attachment_by_ref_tool: Fetch a specific attachment by ID and return its content base64-encoded inline. Refuses files larger than TAIGA_MAX_INLINE_ATTACHMENT_BYTES (default 10 MB) — for larger files use list_attachments_by_ref_tool and curl the download_url out-of-band.
• promote_issue_to_userstory_tool: Promotes an issue to a user story, preserving comments and history.
• list_custom_attributes_tool: Lists custom-attribute definitions for a project + entity type, including dropdown choices (parsed) and the raw extra field — so an agent can discover the valid options for a dropdown attribute before writing via set_custom_attributes_tool.
• set_custom_attributes_tool: Sets custom-attribute values on a user story, task or issue.
• get_custom_attributes_tool: Reads custom-attribute values from a user story, task or issue.
• sort_kanban_by_rice_tool: Re-orders Kanban swimlanes using a RICE-style score. Closed status columns (Done, Cancelled, …) are skipped — re-ranking already-completed work has no value. Each entry in columns_updated carries status_name alongside status_id so consumers don't need to round-trip through Taiga to translate the id.
• set_userstory_points_tool: Sets Taiga story points on a user story for one or more roles (Developer, UX, Design, …). Resolves role names + point values to internal IDs at runtime so it adapts to per-project scales. The only programmatic path to set the field that sort_kanban_by_rice_tool reads as effort. The target role must be configured as computable in the project (Taiga admin → Members → Roles → "Compute story points for this role"); non-computable roles are rejected upfront with a 400 + non_computable_roles diagnostic, instead of letting Taiga's PATCH endpoint return its cryptic Invalid role id server-side rejection (which would otherwise surface as a generic 500 via this tool's exception wrapper).
• list_wiki_pages_tool: Lists wiki pages in a project.
• get_wiki_page_tool: Reads a wiki page by slug.
• create_wiki_page_tool: Creates a wiki page.
• update_wiki_page_tool: Updates a wiki page.
• whoami_tool: Returns the currently authenticated Taiga user.
• list_project_members_tool: Lists all members of a project with their roles (email opt-in).

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Installation

pip install -U langchain-taiga

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Environment Variables

For direct LangChain tool use, the toolkit, and stdio MCP mode (single-user, local credentials):

export TAIGA_URL="https://taiga.xyz.org/"
export TAIGA_API_URL="https://taiga.xyz.org/"
export TAIGA_USERNAME="username"
export TAIGA_PASSWORD="pw"
export OPENAI_API_KEY="..."   # used by some tools' LLM-powered helpers

If TAIGA_USERNAME / TAIGA_PASSWORD are not set, the tools raise ValueError on call.

Remote MCP mode is different — see the Remote Mode section. There, end-users supply their own Taiga credentials interactively at the <mcp-path>/oauth/login form (e.g. https://your-server/mcp/oauth/login); only TAIGA_API_URL, TAIGA_URL, TAIGA_MCP_BASE_URL, and OPENAI_API_KEY are server-side env.

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Usage

Direct Tool Usage

Each tool is a @tool-decorated function callable via .invoke({...}). A few representative examples:

from langchain_taiga.tools.taiga_tools import (
    create_entity_tool,
    search_entities_tool,
    whoami_tool,
)

# Create — write
create_entity_tool.invoke({
    "project_slug": "shikenso-development",
    "entity_type": "us",
    "subject": "Add /metrics endpoint",
    "status": "New",
    "description": "Prometheus-scrape-friendly text format.",
    "tags": ["backend", "observability"],
})

# Search — natural-language query, server-side caps + truncation flag in response
search_entities_tool.invoke({
    "project_slug": "shikenso-development",
    "query": "open issues created after 2026-03-01",
    "entity_type": "issue",
    "max_results": 50,
})

# Whoami — verify auth wiring end-to-end
whoami_tool.invoke({})

For the full set of 21 tools see the list at the top of this README, the docstrings in taiga_tools.py, or just grab them all via the toolkit below.

Using the Toolkit

You can also use TaigaToolkit to automatically gather both tools:

from langchain_taiga.toolkits import TaigaToolkit

toolkit = TaigaToolkit()
tools = toolkit.get_tools()

MCP Server

The package ships an MCP server powered by fastmcp. All 21 tools above are exposed as MCP tools without changing their behaviour. There are two transport modes with different auth models:

Mode	Transport	Auth	Use case
Stdio	stdin/stdout	env-var credentials	One developer running locally — Claude Desktop, Claude Code, VSCode local
Remote	HTTP (streamable)	OAuth 2.1 + PKCE + DCR	Multi-tenant — claude.ai Custom Connectors, VSCode Web, hosted teams

Stdio Mode (single-user, local)

Run the server:

python -m langchain_taiga.mcp_server

Or without installing into your project (using uv):

uv run --with langchain-taiga python -m langchain_taiga.mcp_server

The Taiga credentials come from the TAIGA_USERNAME / TAIGA_PASSWORD env vars set in the wrapping process. All requests use the same single user.

VSCode

Add the following to your .vscode/mcp.json (or via the VSCode MCP settings UI):

{
  "servers": {
    "taiga": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "langchain-taiga",
        "python",
        "-m",
        "langchain_taiga.mcp_server"
      ],
      "env": {
        "TAIGA_API_URL": "${input:taiga_api_url}",
        "TAIGA_URL": "${input:taiga_url}",
        "TAIGA_USERNAME": "${input:taiga_username}",
        "TAIGA_PASSWORD": "${input:taiga_password}"
      }
    }
  },
  "inputs": [
    {
      "id": "taiga_api_url",
      "type": "promptString",
      "description": "Taiga API URL (e.g. https://api.taiga.io)",
      "password": false
    },
    {
      "id": "taiga_url",
      "type": "promptString",
      "description": "Taiga Web URL (e.g. https://tree.taiga.io)",
      "password": false
    },
    {
      "id": "taiga_username",
      "type": "promptString",
      "description": "Taiga Username",
      "password": false
    },
    {
      "id": "taiga_password",
      "type": "promptString",
      "description": "Taiga Password",
      "password": true
    }
  ]
}

Claude Code

Add the Taiga MCP server via the CLI:

claude mcp add taiga -- uv run --with langchain-taiga python -m langchain_taiga.mcp_server

This adds the server to your project's .claude/mcp.json. Make sure the Taiga environment variables are set in your shell, or pass them explicitly:

claude mcp add taiga -e TAIGA_API_URL=https://api.taiga.io -e TAIGA_URL=https://tree.taiga.io -e TAIGA_USERNAME=your_user -e TAIGA_PASSWORD=your_pass -- uv run --with langchain-taiga python -m langchain_taiga.mcp_server

Alternatively, add the entry manually to .claude/mcp.json:

{
  "mcpServers": {
    "taiga": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "langchain-taiga",
        "python",
        "-m",
        "langchain_taiga.mcp_server"
      ],
      "env": {
        "TAIGA_API_URL": "https://api.taiga.io",
        "TAIGA_URL": "https://tree.taiga.io",
        "TAIGA_USERNAME": "your_user",
        "TAIGA_PASSWORD": "your_pass"
      }
    }
  }
}

Claude Desktop / GitHub Copilot Chat

Add a similar entry to your MCP configuration, pointing to uv run --with langchain-taiga python -m langchain_taiga.mcp_server.

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Remote Mode (multi-tenant, OAuth)

Run the server as a long-lived HTTP service:

TAIGA_API_URL=https://taiga.example.org \
TAIGA_URL=https://taiga.example.org \
TAIGA_MCP_BASE_URL=https://mcp.example.org/mcp \
OPENAI_API_KEY=sk-... \
langchain-taiga-mcp-remote

The server speaks MCP over the streamable-HTTP transport at the URL given by TAIGA_MCP_BASE_URL and implements:

• OAuth 2.1 + PKCE (S256) — /authorize, /token
• OAuth 2.1 refresh-token rotation with reuse-detection (2.5.0+) — connected MCP clients (claude.ai, VSCode, Claude Desktop) stay authenticated across hours without forcing the user back through the OAuth flow. Each refresh rotates the token; a replayed refresh token revokes the entire token family per OAuth 2.1 best practice for public clients.
• RFC 7591 Dynamic Client Registration — /register
• RFC 8414 / RFC 9728 discovery docs — /.well-known/oauth-authorization-server[/<mcp-path>] and /.well-known/oauth-protected-resource[/<mcp-path>]
• A login form at <mcp-path>/oauth/login where each user signs in with their own Taiga credentials. The Taiga JWT is then carried per-request via the MCP AccessToken claims and used by every tool call — so two users connected to the same server see only their own projects.

OAuth state lives in-process (per-pod in-memory dict). For production, run a single replica; users re-authorize after a Helm deploy or pod restart (refresh tokens are wiped along with everything else).

Connecting clients to a remote server

Client	How to connect
claude.ai	Settings → Connectors → Add custom connector → URL https://your-server/mcp → sign in with Taiga creds. Anthropic docs.
VSCode (stable + Insiders + Web)	MCP UI → "Add server" → HTTP → https://your-server/mcp. DCR runs automatically; the redirect URIs (vscode.dev/redirect, insiders.vscode.dev/redirect, 127.0.0.1:<port>) are pre-allowed by the server's allowlist.
Claude Desktop	MCP config: "transport": {"type": "http", "url": "https://your-server/mcp"}
MCP Inspector	npx @modelcontextprotocol/inspector → URL https://your-server/mcp → "Quick OAuth Flow"

Production deployment

For Shikenso's deployment to OVH MKS, see the taiga repo's deployment/helm/taiga-mcp chart and Jenkinsfile. Bump the chart's TAIGA_MCP_VERSION parameter after each langchain-taiga release.

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Tests

The CI-aligned command (matches make test in CI):

make test
# expands to:
poetry run pytest --disable-socket --allow-unix-socket tests/unit_tests/

The --disable-socket flag blocks real network calls — the unit tests rely on it being on. Running pytest without it can hide tests that accidentally talk to live services.

For Shikenso's conda env (alternative local setup): source ~/miniconda3/etc/profile.d/conda.sh && conda activate langchain_taiga && python -m pytest --disable-socket --allow-unix-socket tests/unit_tests/.

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License

MIT License

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Further Documentation

• AGENTS.md in this repo — onboarding for AI coding assistants and humans (test command, CI flow, MCP-SDK gotchas, architecture pointers).
• Tool docstrings in langchain_taiga/tools/taiga_tools.py.
• TaigaToolkit.
• Remote OAuth bridge entry point: langchain_taiga/remote_server.py.
• Official Taiga Developer Docs: https://docs.taiga.io/api.html.
• LangChain GitHub for general LangChain usage.
• Model Context Protocol spec.