Search Memories

POST /v1/search — Full-text search without embedding costs.

POST /v1/search

Search Memories

cURL

curl --request POST \
  --url https://api.memoclaw.com/v1/search \
  --header 'Content-Type: application/json' \
  --data '
{
  "query": "<string>",
  "limit": 123,
  "namespace": "<string>",
  "memory_type": "<string>",
  "tags": [
    "<string>"
  ],
  "session_id": "<string>",
  "agent_id": "<string>"
}
'

import requests

url = "https://api.memoclaw.com/v1/search"

payload = {
    "query": "<string>",
    "limit": 123,
    "namespace": "<string>",
    "memory_type": "<string>",
    "tags": ["<string>"],
    "session_id": "<string>",
    "agent_id": "<string>"
}
headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    query: '<string>',
    limit: 123,
    namespace: '<string>',
    memory_type: '<string>',
    tags: ['<string>'],
    session_id: '<string>',
    agent_id: '<string>'
  })
};

fetch('https://api.memoclaw.com/v1/search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.memoclaw.com/v1/search",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'query' => '<string>',
    'limit' => 123,
    'namespace' => '<string>',
    'memory_type' => '<string>',
    'tags' => [
        '<string>'
    ],
    'session_id' => '<string>',
    'agent_id' => '<string>'
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.memoclaw.com/v1/search"

	payload := strings.NewReader("{\n  \"query\": \"<string>\",\n  \"limit\": 123,\n  \"namespace\": \"<string>\",\n  \"memory_type\": \"<string>\",\n  \"tags\": [\n    \"<string>\"\n  ],\n  \"session_id\": \"<string>\",\n  \"agent_id\": \"<string>\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.memoclaw.com/v1/search")
  .header("Content-Type", "application/json")
  .body("{\n  \"query\": \"<string>\",\n  \"limit\": 123,\n  \"namespace\": \"<string>\",\n  \"memory_type\": \"<string>\",\n  \"tags\": [\n    \"<string>\"\n  ],\n  \"session_id\": \"<string>\",\n  \"agent_id\": \"<string>\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.memoclaw.com/v1/search")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"query\": \"<string>\",\n  \"limit\": 123,\n  \"namespace\": \"<string>\",\n  \"memory_type\": \"<string>\",\n  \"tags\": [\n    \"<string>\"\n  ],\n  \"session_id\": \"<string>\",\n  \"agent_id\": \"<string>\"\n}"

response = http.request(request)
puts response.read_body

200

{
  "memories": [
    {
      "id": "<string>",
      "content": "<string>",
      "importance": 123,
      "memory_type": "<string>",
      "namespace": "<string>",
      "tags": [
        "<string>"
      ],
      "created_at": "<string>"
    }
  ],
  "total": 123,
  "query": "<string>"
}

This endpoint requires wallet authentication for identity. It is free — no payment required.

Price: FREE

Full-text keyword search using BM25 ranking. A lightweight alternative to /v1/recall when you don’t need semantic embeddings or want to reduce costs.

This endpoint uses PostgreSQL full-text search (tsvector) rather than vector similarity, making it faster and free from embedding API costs.

Request Body

query · string · required

Search query string. Max 1,000 characters.

limit · number

Maximum number of results. Default: 10. Max: 100.

namespace · string

Filter by namespace.

memory_type · string

Filter by memory type: correction, preference, decision, project, observation, or general.

tags · string[]

Filter by tags.

session_id · string

Filter by session ID.

agent_id · string

Filter by agent ID.

Response (200 OK)

memories · array

Array of matching memories sorted by BM25 relevance.

Show Memory object

id · string

UUID of the memory.

content · string

Memory text content.

importance · number

Importance score (0-1).

memory_type · string

Memory type.

namespace · string

Namespace.

tags · string[]

Tags.

created_at · string

ISO 8601 timestamp.

total · number

Total number of matches.

query · string

The search query used.

When to Use Search vs Recall

Use Case	Endpoint
Natural language semantic search	/v1/recall
Keyword/exact match search	/v1/search
Need vector similarity scoring	/v1/recall
Reduce embedding API costs	/v1/search
Find memories with specific words	/v1/search

Example

curl

curl -X POST https://api.memoclaw.com/v1/search \
  -H "Content-Type: application/json" \
  -H "x-wallet-auth: 0xYourWallet:1699900000:0xSignature..." \
  -d '{
    "query": "dark mode preferences",
    "limit": 10,
    "tags": ["preferences"]
  }'

const response = await fetch("https://api.memoclaw.com/v1/search", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-wallet-auth": await getAuthHeader(),
  },
  body: JSON.stringify({
    query: "dark mode preferences",
    limit: 10,
    tags: ["preferences"],
  }),
});
const data = await response.json();

from memoclaw import MemoClaw

client = MemoClaw()

result = client.search(
    query="dark mode preferences",
    limit=10,
    tags=["preferences"],
)
for m in result.memories:
    print(f"[{m.id}] {m.content}")

import { MemoClawClient } from "memoclaw";

const client = new MemoClawClient();

const result = await client.search({
  query: "dark mode preferences",
  limit: 10,
  tags: ["preferences"],
});
result.memories.forEach(m => {
  console.log(`[${m.id}] ${m.content}`);
});

Response

{
  "memories": [
    {
      "id": "550e8400-e29b-41d4-a716-446655440000",
      "content": "User prefers dark mode",
      "importance": 0.8,
      "memory_type": "preference",
      "namespace": "default",
      "tags": ["preferences", "ui"],
      "created_at": "2026-02-13T10:30:00Z"
    }
  ],
  "total": 1,
  "query": "dark mode preferences"
}