fleet-memory/hindsight-docs/versioned_docs/version-0.5/developer/mcp-server.md
Nicolò Boschi 27cb7e43e0 Release v0.5.0
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MCP Server

Hindsight includes a built-in Model Context Protocol (MCP) server that allows AI assistants to store and retrieve memories directly.

Access

The MCP server is enabled by default and mounted at /mcp on the API server. Each memory bank has its own MCP endpoint:

http://localhost:8888/mcp/{bank_id}/

For example, to connect to the memory bank alice:

http://localhost:8888/mcp/alice/

To disable the MCP server, set the environment variable:

export HINDSIGHT_API_MCP_ENABLED=false

Authentication

By default, the MCP endpoint is open (no authentication required).

To enable authentication, configure the API key tenant extension:

export HINDSIGHT_API_TENANT_EXTENSION=hindsight_api.extensions.builtin.tenant:ApiKeyTenantExtension
export HINDSIGHT_API_TENANT_API_KEY=your-secret-key

When authentication is enabled, include your API key in the Authorization header:

Claude Code

claude mcp add --transport http hindsight http://localhost:8888/mcp \
  --header "Authorization: Bearer your-secret-key" \
  --header "X-Bank-Id: my-bank"

Claude Desktop

Add to ~/.claude_desktop_config.json:

{
  "mcpServers": {
    "hindsight": {
      "url": "http://localhost:8888/mcp",
      "headers": {
        "Authorization": "Bearer your-secret-key",
        "X-Bank-Id": "my-bank"
      }
    }
  }
}

Direct HTTP Request

curl -X POST http://localhost:8888/mcp \
  -H "Authorization: Bearer your-secret-key" \
  -H "X-Bank-Id: my-bank" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc": "2.0", "method": "tools/list", "id": 1}'

If the key is missing or invalid, requests will receive a 401 Unauthorized response.

Bank Selection

The memory bank is resolved in this priority order:

  1. URL path (highest priority): http://localhost:8888/mcp/my-bank/
  2. X-Bank-Id header: --header "X-Bank-Id: my-bank"
  3. Default: Uses HINDSIGHT_MCP_BANK_ID env var (default: "default")

Per-Bank Endpoints

Unlike traditional MCP servers where tools require explicit identifiers, Hindsight uses per-bank endpoints. The bank_id is part of the URL path, so tools don't need to specify which bank to use—it's implicit from the connection.

This design:

  • Simplifies tool usage — no need to pass bank_id with every call
  • Enforces isolation — each MCP connection is scoped to a single bank
  • Enables multi-tenant setups — connect different users to different endpoints

Two Modes

The MCP server operates in two modes depending on the URL:

Mode URL Tools bank_id
Single-bank /mcp/{bank_id}/ 26 tools (memory, mental models, directives, documents, operations, tags, bank management) Implicit from URL
Multi-bank /mcp/ All 29 tools including list_banks, create_bank, get_bank_stats Explicit bank_id parameter on each tool

Single-bank mode (recommended) scopes all operations to the bank in the URL. Tools don't expose a bank_id parameter.

Multi-bank mode exposes all tools with an optional bank_id parameter, plus bank management tools (list_banks, create_bank, get_bank_stats).


Available Tools

retain

Store information to long-term memory.

Parameter Type Required Description
content string Yes The fact or memory to store
context string No Category for the memory (default: general)
timestamp string No ISO 8601 timestamp for when the event occurred
tags list[string] No Tags for organizing and filtering this memory
metadata object No Key-value metadata to attach (e.g., {"source": "slack"})
document_id string No Associate this memory with an existing document

Example:

{
  "name": "retain",
  "arguments": {
    "content": "User prefers Python over JavaScript for backend development",
    "context": "programming_preferences",
    "tags": ["user:alice", "preferences"]
  }
}

When to use:

  • User shares personal facts, preferences, or interests
  • Important events or milestones are mentioned
  • Decisions, opinions, or goals are stated
  • Work context or project details are discussed

recall

Search memories to provide personalized responses.

Parameter Type Required Description
query string Yes Natural language search query
max_tokens integer No Maximum tokens to return (default: 4096)
budget string No Search thoroughness: low, mid, or high (default: high)
types list[string] No Filter by fact type: world, experience, opinion. Defaults to all
tags list[string] No Filter memories by tags
tags_match string No Tag matching mode: any (default) or all
query_timestamp string No ISO 8601 timestamp — recall as if asking at this point in time

Example:

{
  "name": "recall",
  "arguments": {
    "query": "What are the user's programming language preferences?",
    "tags": ["preferences"],
    "budget": "high"
  }
}

When to use:

  • Start of conversation to recall relevant context
  • Before making recommendations
  • When user asks about something they may have mentioned before
  • To provide continuity across conversations

reflect

Generate thoughtful analysis by synthesizing stored memories with the bank's personality.

Parameter Type Required Description
query string Yes The question or topic to reflect on
context string No Optional context about why this reflection is needed
budget string No Search budget: low, mid, or high (default: low)
max_tokens integer No Maximum tokens in the response (default: 4096)
response_schema object No JSON Schema for structured output. When provided, the response includes a structured_output field
tags list[string] No Filter memories by tags before reflecting
tags_match string No Tag matching mode: any (default) or all

Example:

{
  "name": "reflect",
  "arguments": {
    "query": "Based on my past decisions, what architectural style do I prefer?",
    "budget": "mid",
    "tags": ["architecture"]
  }
}

When to use:

  • When reasoned analysis is needed, not just fact retrieval
  • Questions like "What should I do?" rather than "What did I say?"
  • Synthesizing patterns across multiple memories

create_mental_model

Create a mental model — a living document that stays current with your memories. Mental models are pre-computed reflections that get automatically refreshed as new memories are stored.

Parameter Type Required Description
name string Yes Human-readable name for the mental model
source_query string Yes The query used to generate and refresh the model
mental_model_id string No Custom ID (alphanumeric lowercase with hyphens). Auto-generated if not provided
tags list[string] No Tags for organizing and filtering models
max_tokens integer No Maximum tokens for model content (default: 2048)
trigger_refresh_after_consolidation boolean No Auto-refresh this model after memory consolidation (default: false)

Example:

{
  "name": "create_mental_model",
  "arguments": {
    "name": "Team Directory",
    "source_query": "Who works here and what do they do?",
    "tags": ["team", "people"]
  }
}

Content generation runs asynchronously. The response includes an operation_id to track progress.


list_mental_models

List all mental models in a bank, optionally filtered by tags.

Parameter Type Required Description
tags list[string] No Filter models by tags

get_mental_model

Retrieve a specific mental model by ID, including its full content.

Parameter Type Required Description
mental_model_id string Yes The ID of the mental model to retrieve

update_mental_model

Update a mental model's metadata or settings.

Parameter Type Required Description
mental_model_id string Yes The ID of the mental model to update
name string No New name
source_query string No New source query
tags list[string] No New tags
max_tokens integer No New max tokens
trigger_refresh_after_consolidation boolean No Auto-refresh after consolidation. Only set when you want to change this setting

delete_mental_model

Permanently delete a mental model.

Parameter Type Required Description
mental_model_id string Yes The ID of the mental model to delete

refresh_mental_model

Re-generate a mental model's content from the latest memories. Runs asynchronously.

Parameter Type Required Description
mental_model_id string Yes The ID of the mental model to refresh

list_banks (multi-bank mode only)

List all available memory banks.


create_bank (multi-bank mode only)

Create a new memory bank or retrieve an existing one.

Parameter Type Required Description
bank_id string Yes The ID for the new bank
name string No Human-friendly name for the bank
mission string No Mission describing who the agent is and what they're trying to accomplish

list_directives

List all directives in a bank. Directives are instructions that guide how the memory system processes and responds to queries.

Parameter Type Required Description
tags list[string] No Filter directives by tags
active_only boolean No Only return active directives (default: true)

create_directive

Create a new directive in a bank.

Parameter Type Required Description
name string Yes Human-readable name for the directive
content string Yes The directive content/instruction
priority integer No Priority level (higher = more important)
is_active boolean No Whether the directive is active (default: true)
tags list[string] No Tags for organizing directives

delete_directive

Delete a directive by ID.

Parameter Type Required Description
directive_id string Yes The ID of the directive to delete

list_memories

Browse stored memories with optional filtering and pagination.

Parameter Type Required Description
type string No Filter by fact type: world, experience, or opinion
q string No Search query to filter memories
limit integer No Maximum number of results (default: 100)
offset integer No Number of results to skip for pagination (default: 0)

get_memory

Retrieve a specific memory by ID.

Parameter Type Required Description
memory_id string Yes The ID of the memory to retrieve

delete_memory

Permanently delete a specific memory.

Parameter Type Required Description
memory_id string Yes The ID of the memory to delete

list_documents

List documents that have been ingested into the memory bank.

Parameter Type Required Description
q string No Search query to filter documents
limit integer No Maximum number of results (default: 100)

get_document

Retrieve a specific document by ID, including its metadata.

Parameter Type Required Description
document_id string Yes The ID of the document to retrieve

delete_document

Delete a document and all memories linked to it.

Parameter Type Required Description
document_id string Yes The ID of the document to delete

list_operations

List async operations (retain processing, mental model refresh, etc.) with optional status filtering.

Parameter Type Required Description
status string No Filter by status: pending, running, completed, failed, cancelled
limit integer No Maximum number of results (default: 100)

get_operation

Get the status and details of an async operation.

Parameter Type Required Description
operation_id string Yes The ID of the operation to check

cancel_operation

Cancel a pending or running async operation.

Parameter Type Required Description
operation_id string Yes The ID of the operation to cancel

list_tags

List all unique tags used in a bank, optionally filtered by pattern.

Parameter Type Required Description
q string No Glob pattern to filter tags (e.g., project:*)
limit integer No Maximum number of results (default: 100)

get_bank

Get information about a memory bank, including its name, mission, and disposition.


get_bank_stats (multi-bank mode only)

Get statistics for a memory bank (node/link counts).


update_bank

Update a memory bank's metadata.

Parameter Type Required Description
name string No New human-friendly name for the bank
mission string No New mission describing who the agent is and what they're trying to accomplish

delete_bank

Permanently delete a memory bank and all its data (memories, documents, entities, mental models).


clear_memories

Clear all memories from a bank without deleting the bank itself. Optionally filter by fact type to only clear specific kinds of memories.

Parameter Type Required Description
type string No Fact type to clear: world, experience, or opinion. If not specified, clears all

Integration with AI Assistants

The MCP server can be used with any MCP-compatible AI assistant. See the Authentication section above for Claude Code and Claude Desktop configuration examples.

Each user can have their own configuration pointing to their personal memory bank using either:

  • A bank-specific URL path like /mcp/alice/ (recommended)
  • The X-Bank-Id header