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When your agent is connected to multiple servers, it may not know what information is available in each one. Context Maps solve this by providing a structured, semantic overview of the data landscape across all connected servers.

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What it does

When enabled, the Navigator exposes a get_context_map MCP tool to your agent. Calling this tool returns a set of cards — each summarizing the type of information available in a connected server — along with relations between cards that highlight cross-server connections. For example, a Context Map might tell your agent:
  • Slack has recent engineering discussions about deployment issues and customer feedback from the past 7 days
  • Linear has active sprint items including 3 bug reports and 12 feature requests from the past 14 days
  • Relation: Slack engineering discussions reference Linear issues, with a 0.82 similarity score
This helps your agent understand where to look before making queries, rather than blindly trying tools until it finds the right data.

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How to enable

1

Ensure extraction is configured

Context Maps require at least 2 server instances in the project with data extraction enabled. Extraction configuration is managed per server instance and defines which tools to use for data exploration and how frequently to update.
2

Enable Context Maps on the Navigator Instance

Go to the Navigator Instance settings and toggle Context Maps to on.
The get_context_map tool only appears in your agent’s tool list if the project has 2 or more context map cards available. If fewer than 2 servers have been explored, the tool is hidden.

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How it works

Context Maps are built through a background extraction process:
  1. Data exploration — Caylex uses read-only tools on each server to explore what data is available. For example, it might list recent Slack channels, browse Linear issues, or search Notion pages.
  2. Card generation — for each server, Caylex generates a card summarizing the information found. Each card includes:
    • Title — a descriptive name (e.g., “Engineering Issue Tracking”)
    • Summary — a 2-4 sentence overview of what information exists
    • Sample entities — example items discovered (e.g., teams, projects, channels)
    • Freshness — how recently the card was updated
    • Coverage — the time span of data covered (e.g., “last 7 days”)
  3. Relation detection — Caylex compares cards using semantic similarity to find cross-server connections. Relations describe how information in one server relates to information in another.
  4. Periodic updates — cards are refreshed on a configurable cadence (default: every 7 days) to keep the map current.

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The get_context_map response

When your agent calls get_context_map, the response includes: 
{
  "cards": [
    {
      "server_name": "Slack",
      "title": "Team Communication",
      "summary": "Recent messages across 5 active channels covering engineering discussions, customer support, and product planning.",
      "sample_entities_found": {
        "channels": ["#engineering", "#support", "#product"],
        "topics": ["deployment", "bug fixes", "Q1 planning"]
      },
      "card_information_freshness": "2 hours ago",
      "coverage_note": "Last 7 days"
    },
    {
      "server_name": "Linear",
      "title": "Engineering Issue Tracking",
      "summary": "Active sprint with 15 issues across 2 teams. Includes bug reports, feature requests, and infrastructure tasks.",
      "sample_entities_found": {
        "teams": ["Platform", "Frontend"],
        "labels": ["bug", "feature", "infrastructure"]
      },
      "card_information_freshness": "1 day ago",
      "coverage_note": "Last 14 days"
    }
  ],
  "relations": [
    {
      "from_card": "Slack",
      "to_card": "Linear",
      "description": "Engineering discussions in Slack frequently reference Linear issues and sprint progress.",
      "similarity": 0.82
    }
  ]
}

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Extraction configuration

Each server instance can be configured with extraction settings that control how Context Maps explore the server:
SettingDescriptionDefault
Extraction instructionsGuidance for how to explore the serverAuto-generated
Time windowHow far back to look for data7 days
Max tool callsMaximum number of tool calls per extraction run20
Max responses to keepNumber of significant responses to retain10
Update cadenceHow often to refresh the card7 days
Read-only toolsWhich tools to use for exploration (read-only only)Auto-detected
For servers with large amounts of data, increasing the time window and max tool calls gives Context Maps a broader view of available information. For frequently changing data, reduce the update cadence to keep cards fresh.

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When to enable Context Maps

ScenarioRecommendation
Agent connects to 3+ diverse servers (e.g., Slack + Linear + Notion)Enable — helps the agent navigate across information silos
Agent connects to a single serverDisable — not useful with only one source of information
Agent handles open-ended research or analysis queriesEnable — the agent benefits from knowing what data is available before diving in
Agent performs targeted, specific operationsOptional — may not need a high-level overview