Connect a Slack bot to Linear
Verified August 11, 2026
This gives a Slack bot access to Linear. Ask it a question in a channel and it will read and file issues in your Linear workspace and answer in the thread.
What you need
- A Slack workspace where you can install apps
- A Linear account
- An OpenRouter account
Install the CLI
npm i -g @substructure.ai/cliWrite the config
Save this as substructure.toml.
name = "planner-bot"
[llm.openrouter]
type = "openrouter"
[mcp.linear]
url = "https://mcp.linear.app/mcp"
[agent.planner]
llm = "openrouter"
model = "z-ai/glm-5.2"
system = "You are the planning assistant. Answer questions about Linear issues and file them when asked."
mcp = ["linear"]
[slack]
dm = "planner"
mentions = "planner"
[remote]
url = "https://api.substructure.ai"[agent.planner] declares the agent: its model, its prompt, and the connections it can reach. The Slack bot is how you talk to it.
The file holds the server URL and the agent that uses it. It holds no tokens.
[remote] is the deployment the CLI talks to. subs apply writes the org and the project back under it.
Create the project
subs applyThis creates the project from the file and writes the project id back into it. If you are not signed in yet, the command opens your browser first. Run subs apply again after any edit to the file.
Add your LLM key
subs llm set-key openrouterThe agent's model runs through OpenRouter, so it needs an OpenRouter API key. Create one at openrouter.ai/keys if you do not have one. The command stores the key with your deployment. It never goes in the config file.
Authorize Linear
subs mcp login linearThis opens Linear's consent page. Approve it and the credential goes to your deployment.
Run subs mcp list to check the connection is authorized.
Connect Slack
subs slack connectPick your workspace and approve. The bot is live once the command prints the workspace name.
Ask it something
Invite the bot to a channel and mention it.
- "what is in this cycle?"
- "file a bug about the login redirect"
Each tool call shows in the thread as a task card. Open a card to see the arguments and the result.
Limit the tools
An id on its own takes every tool the server offers. A model picks worse as the tool list grows. Use the table form to take fewer.
[agent.planner]
mcp = [{ id = "linear", tools = { read_only = true } }]If it does not answer
- Connection not authorized. Run
subs mcp list. A declared connection with no credential reaches nothing. - No
[slack]section. A connected workspace with no[slack]never replies. - Bot not invited. Invite it to the channel before you mention it.
- Tools missing. The engine fetches the tool list once per session. Start a new thread after you change the filter.
- Anything else. Run
subs doctor.
Add another server
Declare it and name it on the agent.
[mcp.linear]
url = "https://mcp.linear.app/mcp"
[mcp.linear]
url = "https://mcp.linear.app/mcp"
[agent.planner]
mcp = ["linear", "linear"]Tools arrive prefixed with the connection id, such as linear__search.
The same setup works for Sentry, GitHub, Notion, Stripe, and each has its own guide. See all guides.
Next steps
- Run the bot on an open model: Kimi K3 and the rest, with prices and what a thread costs.
- How MCP connectors work: auth, tool fetching, and filters.
- Build your own tools when a hosted server is not enough.
- Pricing: one flat price a month, and no per-token charges from us.