Skip to content

Latest commit

 

History

History
84 lines (84 loc) · 3.48 KB

File metadata and controls

84 lines (84 loc) · 3.48 KB

Engram MCP Server Integration Guide

====================================

How to replace chat2mem with Engram in Army of the Agent config.yaml

CURRENT (chat2mem via remote SSE):

- name: "chat2mem"

transport: sse

access_token: "ThIZ5f5GfXGk4lzYi0XQuxrVAftESL6k-JPUGAXaqcM"

REPLACEMENT (Engram via local stdio):

- name: "engram"

transport: stdio

command: /data/armyoftheagent/engram/engram

args: ["serve"]

env:

ENGRAM_QDRANT_URL: "localhost:6334"

ENGRAM_OPENAI_API_KEY: ""

ENGRAM_OPENAI_BASE_URL: "https://api.openai.com/v1"

ENGRAM_EMBEDDING_MODEL: "text-embedding-3-small"

ENGRAM_EMBEDDING_DIMENSION: "1536"

ENGRAM_TRANSPORT: "stdio"

TOOL NAME MAPPING:

==================

chat2mem → Engram

─────────────────────────────────────────

retrieve_memory → memory.search

add_memory → memory.add

update_memory → memory.update

delete_memory → memory.delete

update_relationship → (use memory.update with tags)

list_due_followups → (use memory.search with tag filter)

PARAMETER MAPPING:

==================

chat2mem retrieve_memory → Engram memory.search

query → query

memory_type → types (array, mapped: fact→identity, topic/observation→event, reflection→insight)

limit → limit

time_start → time_start

time_end → time_end

event_date_from → (use tags or metadata)

event_date_to → (use tags or metadata)

chat2mem add_memory → Engram memory.add

content → content

type → type (mapped: fact/preference→identity, topic/observation/plan/study→event, reflection→insight)

importance → importance

event_date → (store in tags or metadata)

MEMORY TYPE MAPPING:

====================

chat2mem → Engram

─────────────────────────────────────────

fact → identity (tag: fact)

preference → identity (tag: preference)

topic → event (tag: topic)

observation → event (tag: observation)

plan → event (tag: plan)

study → event (tag: study)

reflection → insight

relationship → identity (tag: relationship)

PREREQUISITES:

==============

1. Qdrant running on localhost:6334

docker run -d --name engram-qdrant --security-opt seccomp=unconfined \

-p 6333:6333 -p 6334:6334 \

-v engram_qdrant_data:/qdrant/storage \

qdrant/qdrant:v1.9.7

2. Engram binary built:

cd /data/armyoftheagent/engram && go build -o engram ./cmd/engram/

3. OpenAI API key for embeddings

DATA MIGRATION:

===============

Migration tool (engram migrate) is planned for M5.

It will read from chat2mem's Qdrant collection (memory_stream)

and write to Engram's collection (engram) with type mapping.