Security & Privacy

SignalPilot is designed with security-first principles: read-only access, local-first execution, and zero data retention.

Core Security Principles

Read-Only Access

All MCP connections are read-only — no writes to production systems

Local-First Execution

Code runs in your environment — never on SignalPilot servers

Zero Data Retention

No data stored on SignalPilot servers — full privacy

Audit Trail

Track what context was accessed and when

MCP Read-Only Access Model

SignalPilot uses the Model Context Protocol (MCP) to connect to your data stack:

Internal MCP Sidecar

The internal sidecar runs within your Jupyter environment:

✅ Kernel introspection: Read variables, dataframes
✅ Schema queries: Read table metadata
✅ Query history: Read past queries (no execution)
❌ Database writes: Not possible
❌ File system writes: Not possible (except notebooks)

External MCP Servers

External MCP servers are read-only by design:

Integration	What SignalPilot Can Read	What It Cannot Do
dbt	Model definitions, lineage, docs	Modify models, run dbt commands
Slack	Public channel threads, messages	Post messages, access private DMs
Jira	Tickets, comments, metadata	Create/modify tickets
Snowflake/Databricks	Query logs, metadata	Execute queries, modify data

We recommend using read / view only credentials (db / notions etc.) and MCP tooling for SignalPilot agent to ensure maximum saftey for the agentic harness.

Approval Workflows

SignalPilot includes built-in approval mechanisms:

Agent/Planning Mode

Agent creates a plan and waits for your approval before execution

Use Planning Mode for high-stakes investigations or production queries

Hands-On Mode

Agent suggests code, but you execute manually in cells

Ask Mode

Agent is read-only — no code execution, only answers questions

Hooks: Custom Constraints (Alpha)

Enforce your own rules via pre-execution hooks:

Example: Production Query Hours

# Only allow prod queries during business hours
def validate_query(query, context):
    if is_prod_db(context) and not is_business_hours():
        raise ValidationError("Production queries only allowed 9am-5pm EST")

Example: Row Count Changes

# Warn if row count changes significantly
def check_row_count(result, context):
    if abs(result.row_count - context.expected_count) > 0.2:
        warning("Row count changed by >20% — verify data quality")

Example: Vectorization Enforcement

# Require vectorized pandas operations
def validate_code(code):
    if "for " in code and "df" in code:
        raise ValidationError("Use vectorized pandas operations, not loops")

Data Retention & Privacy

What SignalPilot Stores

Session metadata: Timestamps, user IDs (anonymized)
Error logs: Stack traces (no data values)
Usage metrics: Feature usage, performance

What SignalPilot Does NOT Store

❌ Query results: Never stored on our servers
❌ Database schemas: Read in real-time, not cached
❌ Slack messages: Read via MCP, not stored
❌ Source code: Notebooks stay local

Data in Transit

TLS 1.3: All connections encrypted
API keys: Stored locally, never transmitted
MCP connections: Encrypted via SSH/TLS

SOC 2 Compliance

SignalPilot is working on SOC 2 Type II compliance (status: in progress as of 2026).

We follow industry best practices for:

Access controls and authentication
Data encryption (at rest and in transit)
Incident response and monitoring
Vendor risk management

Questions?

How it works

Understand the Architecture

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Install SignalPilot Securely

Introduction

Getting Started

Integrations

Core Concepts

Security & Privacy

Security & Privacy

Core Security Principles

Read-Only Access

Local-First Execution

Zero Data Retention

Audit Trail

MCP Read-Only Access Model

Internal MCP Sidecar

External MCP Servers

Approval Workflows

Hooks: Custom Constraints (Alpha)

Example: Production Query Hours

Example: Row Count Changes

Example: Vectorization Enforcement

Data Retention & Privacy

SOC 2 Compliance

Questions?

How it works

Get started

​Security & Privacy

​Core Security Principles

Read-Only Access

Local-First Execution

Zero Data Retention

Audit Trail

​MCP Read-Only Access Model

​Internal MCP Sidecar

​External MCP Servers

​Approval Workflows

​Hooks: Custom Constraints (Alpha)

​Example: Production Query Hours

​Example: Row Count Changes

​Example: Vectorization Enforcement

​Data Retention & Privacy

​SOC 2 Compliance

​Questions?

How it works

Get started

Security & Privacy

Core Security Principles

MCP Read-Only Access Model

Internal MCP Sidecar

External MCP Servers

Approval Workflows

Hooks: Custom Constraints (Alpha)

Example: Production Query Hours

Example: Row Count Changes

Example: Vectorization Enforcement

Data Retention & Privacy

SOC 2 Compliance

Questions?