AI Assistant
Chat with an AI assistant that reads and edits your Sling Platform project
The AI Assistant is a chat panel inside the Sling Platform UI. It answers questions about your project and does work in it: it reads files, checks run history, validates YAML, and edits configuration.
The assistant uses the same tools as the MCP Server, so it has the same reach and the same limits. The difference is where it runs. The assistant is built into the UI and speaks to a model endpoint you configure. The MCP server lets an external client, such as Claude Code or Cursor, connect to the project.
Setup
What you set up depends on how you run Sling.
Cloud
Nothing to set up. Sling supplies the model endpoint, so the assistant is ready the moment you open a project.
The assistant is on by default. Switch it off for a project under Settings → AI & MCP → Enable AI Assistant.
Self-hosted
The assistant calls a model endpoint that you supply. Open Settings → AI & MCP and select Configure next to Enable AI Assistant. Fill in the API format, model, endpoint, and API key. The endpoint is used by every project on the server.
Select Test to send a one-token request before you save. After a successful save the launcher appears without a restart.
You can still set the SLING_PLATFORM_ASSISTANT environment variable on the master server instead of (or until) saving in the UI. A saved UI config takes precedence. Clearing the UI config falls back to the environment variable.
The log shows the configuration that loaded:
Configuration reference
The Configure dialog exposes the same fields. Use the environment variable when you prefer to inject the key from the host rather than store it in the database.
model
—
Required. The model name to call. If empty, the assistant stays off.
api_format
openai
anthropic selects the Anthropic adapter. Any other value uses the OpenAI adapter.
base_url
Per format
Endpoint root, with no /v1 path. The adapter adds the route.
api_key
—
The API key, given directly.
api_key_env
—
Name of an environment variable to read the key from. api_key wins if you set both.
max_tokens
8192
Cap on tokens the model generates per reply.
context_tokens
100000
Context budget. The assistant compacts a chat when it passes 60% of this.
headers
—
Extra HTTP headers to send, as a JSON object.
system_extra
—
Text appended to the system prompt. Use it to state project conventions.
web_search
true
Lets the model search the web. Anthropic only.
limits
See below
Per-user daily budget and per-turn caps.
The default base_url is https://api.anthropic.com for the anthropic format and https://api.openai.com otherwise. The OpenAI adapter posts to /v1/chat/completions and the Anthropic adapter posts to /v1/messages.
Because any unrecognized api_format falls back to the OpenAI adapter, an endpoint that implements the OpenAI chat-completions API works with api_format: "openai" and a base_url that points at it.
web_search only takes effect with api_format: "anthropic". The OpenAI adapter ignores it. When on, the model can search the web itself, and the system prompt tells it to prefer the built-in research tool for Sling documentation and to treat web results as untrusted.
Project settings
Open Settings → AI & MCP to control the assistant per project.
Enable AI Assistant
Shows or hides the assistant for this project. On when unset.
Allow Assistant or MCP to view Data
Lets the assistant read table contents. Off by default.
The assistant does not need Enable MCP Server. That setting only controls external MCP clients.
Data access
Without Allow Assistant or MCP to view Data, the assistant reads your configuration but never your data. Four actions stay blocked:
connections.preview— sample rows from a table or fileconnections.exec— run a read-only SQL queryreplications.preview— preview replication outputbuilds.preview— preview SQL model output
A blocked call returns a clear message, and the assistant reports it rather than working around it.
Switch this on only if you accept that table contents reach your model endpoint. Listing tables and reading column names stay available either way, so most questions about structure need no data access.
Using the assistant
Select the sparkle button at the bottom right to open the panel.
Type a question and press Enter. Use Shift + Enter for a new line. The assistant streams its answer and shows each tool call as it runs, so you can see the work behind a reply.
Drag the panel by its header to move it. Drag its bottom-right corner to resize it. The size is remembered; the position resets each time you open it.
Chats
Each conversation is a chat, kept per user and per project. Nobody else sees yours.
Select + to start a new chat.
Select ‹ to go back to the list.
Search the box at the top to find text in earlier chats.
Hover a row and select the bin icon to delete a chat.
What it can do
The assistant reaches the same thirteen tools as the MCP server:
project
Project metadata, dashboard, events, git status and diffs, platform status
files
List, read, write, patch, rename, and delete project YAML and SQL files
jobs
List, save, trigger, activate, and deactivate jobs
executions
Run history, logs, task and step detail, cancel a run
connections
List and test connections, discover objects, preview and query data
replications
Validate replications and preview one stream
pipelines
Validate pipelines
builds
Compile and preview SQL models
monitors
Compile monitors; history, column statistics, events, and schema state
agents
List agents, read metrics, restart or stop an agent
specs
Validate an API spec and test an endpoint against a live agent
research
Read Sling documentation and search public engine issues
guides
Authoring references for each artifact type
Some actions need an agent that is online, because the agent holds the connection credentials. These include every connections action except list, replications.compile/preview, specs.compile/test, monitors.compile, and all of builds. pipelines.compile validates on the server. If no agent is online, the call fails with an agent offline message.
Good questions to ask
The assistant is strongest when a question needs several lookups joined together:
"How do I create a replication from Postgres to Snowflake?"
"Create a SQL model that aggregates daily order totals."
"Validate my replications. Are any of them broken?"
"How do I schedule a job to run this replication every morning at 6am?"
"Which replications failed in the last 24 hours, and why?"
"This job errors with a type mismatch. What is wrong?"
What to check
The assistant writes to your project. It can save files, and it can trigger jobs. Treat its edits like a colleague's pull request: read the diff before you rely on it. Every change it makes is recorded in the project event log, attributed to you, and marked as made through the assistant, so Audit Logs shows exactly what it did.
Quotas
Each user gets a budget per project, counted in chat turns and tokens. Daily counters reset at midnight UTC. The monthly token counter resets on the first of the month. Settings → AI & MCP shows what you used and where the limit comes from.
Self-hosted deployments call their own model endpoint and pay for it directly, so Sling imposes no budget. Set one under Set a Quota if you want a cap. Cloud quotas come from the plan and cannot be changed, because Sling pays for the model calls.
The rest of this section applies to self-hosted only. Change the built-in limits in Configure → Advanced, or through the limits object when using the environment variable:
turns_per_day
100
Chat turns per user per day. 0 means no limit.
tokens_per_day
250000
Tokens per user per day. 0 means no limit.
tokens_per_month
2000000
Tokens per user per month. 0 means no limit.
max_tool_calls
15
Steps the assistant may take in one turn before it must answer.
max_input_chars
8000
Longest single message a user may send.
A separate rate limit guards against bursts, set with SLING_ASSISTANT_RATE_LIMIT (requests per minute, default 10) and SLING_ASSISTANT_RATE_BURST (default 3).
Troubleshooting
The launcher does not appear. On cloud, the project has Enable AI Assistant switched off. On self-hosted, no model endpoint is configured: open Settings → AI & MCP → Configure, or set SLING_PLATFORM_ASSISTANT. Check the server log if an environment payload failed to parse.
"The assistant is not configured on this server." Same cause. The Enable AI Assistant toggle is disabled until a model is configured.
"rate limit exceeded; retry shortly". Too many messages in a short time. Wait a moment.
"agent offline". The action needs an agent to run it. Start an agent, then ask again.
"AI data view is disabled for this project". The action reads data. Switch on Allow Assistant or MCP to view Data.
Related
MCP Server — connect an external AI client to a project
CLI MCP Server — the local stdio server for
env.yamlworkSelf-Hosting — run the platform in your own infrastructure
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