fleet-memory/hindsight-docs/docs/developer/mcp-server.md
DK09876 d8376ecf6b
Fix incorrect MCP tool parameters in docs (#358)
- Remove phantom `max_results` param from recall (only has query + max_tokens)
- Remove `budget` param from local-mcp recall (only reflect has budget)
- Add missing `name` and `mission` optional params to create_bank
- Add missing `mental_model_id` optional param to create_mental_model

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 08:52:05 -07:00

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8.7 KiB
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---
sidebar_position: 5
---
# MCP Server
Hindsight includes a built-in [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) 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:
```bash
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:
```bash
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
```bash
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`:
```json
{
"mcpServers": {
"hindsight": {
"url": "http://localhost:8888/mcp",
"headers": {
"Authorization": "Bearer your-secret-key",
"X-Bank-Id": "my-bank"
}
}
}
}
```
### Direct HTTP Request
```bash
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}/` | Memory + mental model tools | Implicit from URL |
| **Multi-bank** | `/mcp/` | All tools including bank management | 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`).
---
## 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 |
**Example:**
```json
{
"name": "retain",
"arguments": {
"content": "User prefers Python over JavaScript for backend development",
"context": "programming_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) |
**Example:**
```json
{
"name": "recall",
"arguments": {
"query": "What are the user's programming language preferences?"
}
}
```
**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`) |
**Example:**
```json
{
"name": "reflect",
"arguments": {
"query": "Based on my past decisions, what architectural style do I prefer?",
"budget": "mid"
}
}
```
**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) |
**Example:**
```json
{
"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 |
---
### 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 |
---
## Integration with AI Assistants
The MCP server can be used with any MCP-compatible AI assistant. See the [Authentication](#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