Instagram Profile Scraper - Bio & Posts: MCP config, n8n workflow and API
Public Instagram profiles and recent posts become records with author details, captions, hashtags, mentions, media information and engagement counts. Use it to review named accounts alongside their recent publishing activity.
Supply usernames as Instagram handles, with or without @, or as Instagram profile links.
Fastest route, in Claude Code:
claude mcp add --transport http instagram-profile-scraper-bio-and-posts "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts" One click, signs in with Apify on first use:
Any other client, one command (writes the config for 25+ agents, including Windsurf, Zed, Cline and Goose):
npx add-mcp "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts" --name instagram-profile-scraper-bio-and-posts Every file on this page is generated from the Actor's published schema: 51 of 51 checks pass (validated, not run)
- MCP configs: 7 of 7 (Uses Apify's hosted MCP endpoint over HTTPS; The tools parameter lists exactly the chosen Actors as owner/name; JSON configs parse and use the client's top-level key and the same URL; Codex TOML has a [mcp_servers.<name>] table with url and bearer_token_env_var; CLI commands quote the same URL and use the streamable HTTP transport; One-click install links decode back to the same URL and carry no token; Only placeholders, no real token)
- n8n workflow: 11 of 11 (It has a nodes array and a connections object; Every node has a name, type, typeVersion, position and parameters; Node names are unique; Every node type is a known n8n core node (or the Apify node); Every node uses a typeVersion that n8n ships; Every connection points at an existing node; At least one trigger starts the workflow; Every working node is reachable from a trigger; Apify calls use POST and a credential for the token; Actor input matches the Actor's published input schema; No token or credential value is embedded)
- long-run workflow: 11 of 11 (It has a nodes array and a connections object; Every node has a name, type, typeVersion, position and parameters; Node names are unique; Every node type is a known n8n core node (or the Apify node); Every node uses a typeVersion that n8n ships; Every connection points at an existing node; At least one trigger starts the workflow; Every working node is reachable from a trigger; Apify calls use POST and a credential for the token; Actor input matches the Actor's published input schema; No token or credential value is embedded)
- example input: 5 of 5 (All 1 required input field is present; Every input key exists in the published input schema; Every value has the type the schema declares; Every choice field uses one of its published options; Numbers respect the published minimum and maximum)
- code snippets: 4 of 4 (curl calls the documented run-sync-get-dataset-items endpoint for this Actor; Python (apify-client 3.x typed Run) and JavaScript use the official apify-client call() then read the run's dataset; Multi-line shell commands continue every line with a backslash; Token read from APIFY_TOKEN, none embedded)
- SKILL.md: 13 of 13 (SKILL.md starts with YAML front matter; name is 1-64 lowercase letters, digits and single hyphens; name matches the skill folder name; description is present, at most 1024 characters and has no angle brackets; front matter uses only spec fields; compatibility is at most 500 characters; body has instructions; field descriptions end on whole sentences; no credential values are embedded; the token is read from APIFY_TOKEN; the run command calls this Actor's run-sync endpoint; the example input is valid JSON; the example input matches the published input schema)
What a run costs
Every run pays a start fee plus a price per result. On the Free plan this Actor's start fee is $0.20 (the start event, $0.05 per GB, times its default 4 GB of memory), $0.04 on Business; results cost $0.70 per 1,000 results (pay per event). Checked 2026-11-12.
| Results in one run | Start | Results | Run total |
|---|---|---|---|
| 10 | $0.20 | $0.007 | $0.21 |
| 100 | $0.20 | $0.07 | $0.27 |
| 1,000 | $0.20 | $0.70 | $0.90 |
Plus Apify platform usage for the run, which the caller pays. A smaller memory setting lowers the start fee if the Actor still finishes. Prices can change; the Store pricing tab is the source of truth.
MCP config
One URL works in every client: https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts. It exposes this Actor as a tool, plus fetch-actor-details so the agent can read the input schema before calling it. Pick your client:
Claude Code configterminal or .mcp.json
claude mcp add --transport http instagram-profile-scraper-bio-and-posts "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts" Run the command in your project folder. Add --scope user to make it available in every project. Full Claude Code setup
Claude Desktop configclaude_desktop_config.json
{
"mcpServers": {
"instagram-profile-scraper-bio-and-posts": {
"command": "npx",
"args": [
"-y",
"@apify/actors-mcp-server",
"--tools",
"fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts"
],
"env": {
"APIFY_TOKEN": "YOUR_APIFY_TOKEN"
}
}
}
} Easiest: open Customize, then Connectors, choose Add custom connector, paste the server URL (the ChatGPT tab shows it on its own) and sign in to Apify. Full Claude Desktop setup
Cursor config~/.cursor/mcp.json
{
"mcpServers": {
"instagram-profile-scraper-bio-and-posts": {
"url": "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts",
"headers": {
"Authorization": "Bearer ${env:APIFY_TOKEN}"
}
}
}
} Save as ~/.cursor/mcp.json for every project, or .cursor/mcp.json for one project. Merge with servers you already have. Full Cursor setup
VS Code config.vscode/mcp.json
{
"inputs": [
{
"type": "promptString",
"id": "apify-token",
"description": "Apify API token",
"password": true
}
],
"servers": {
"instagram-profile-scraper-bio-and-posts": {
"type": "http",
"url": "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts",
"headers": {
"Authorization": "Bearer ${input:apify-token}"
}
}
}
} Save as .vscode/mcp.json in your workspace. Full VS Code setup
ChatGPT configPlugins > Add custom MCP server
https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts In ChatGPT on the web, open Plugins, select + and choose Add custom MCP server. Full ChatGPT setup
Codex CLI config~/.codex/config.toml
[mcp_servers.instagram-profile-scraper-bio-and-posts]
url = "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts"
bearer_token_env_var = "APIFY_TOKEN" Add the block to ~/.codex/config.toml, or .codex/config.toml in a project. Full Codex CLI setup
Gemini CLI configterminal (writes ~/.gemini/settings.json)
gemini mcp add -t http -s user -H "Authorization: Bearer $APIFY_TOKEN" instagram-profile-scraper-bio-and-posts "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts" Export APIFY_TOKEN first: the shell expands it and Gemini CLI saves the header, token included, in plain text in ~/.gemini/settings.json (keep that file private). In PowerShell write $env:APIFY_TOKEN instead of $APIFY_TOKEN. Drop -s user to save it in the project's .gemini/settings.json. Full Gemini CLI setup
n8n AI Agent configMCP Client Tool node
https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts Add an AI Agent node, then attach an MCP Client Tool node to its tool input. Full n8n AI Agent setup
Tools your agent gets
Listed by Apify's MCP server 0.21.5 for this exact URL on 2026-11-11 (a tools/list call; nothing was run).
fetch-actor-detailsreads the input schemaget-actor-runchecks a run's statusget-dataset-itemsreads a run's resultsget-key-value-store-recordreads a stored record such as a file or summaryabort-actor-runstops a run that is still goingdataspryva--instagram-profile-scraper-bio-and-postsruns the Actor and returns its results
n8n workflow
A manual and a daily trigger call the Actor through the HTTP Request node with your Apify token, then hand each record to the destination you pick. The Actor input sits in the request body, already filled with the example below.
- Run by hand
- Every day
- Run Apify Actor
n8n workflowinstagram-profile-scraper-bio-and-posts.n8n.json
{
"name": "Instagram Profile Scraper - Bio & Posts to n8n only",
"nodes": [
{
"id": "2f77887a-13e3-472c-a079-d42d138314c3",
"name": "Run by hand",
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
0,
0
],
"parameters": {}
},
{
"id": "cadeb57a-3199-4502-a85c-ef3751fdfcb3",
"name": "Every day",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
0,
200
],
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 8
}
]
}
},
"notes": "Activate the workflow to run on this schedule."
},
{
"id": "3efa151e-ea4d-4f1b-ae5e-e6be048a508b",
"name": "Run Apify Actor",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
260,
100
],
"parameters": {
"method": "POST",
"url": "https://api.apify.com/v2/actors/dataspryva~instagram-profile-scraper-bio-and-posts/run-sync-get-dataset-items",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "{\n \"usernames\": [\n \"instagram\"\n ],\n \"maxPosts\": 3\n}",
"options": {
"timeout": 310000
}
},
"notes": "Actor: dataspryva/instagram-profile-scraper-bio-and-posts. Select a Header Auth credential: name Authorization, value Bearer + your Apify token. Edit the JSON body to change the input.",
"notesInFlow": false
},
{
"id": "0b4c4b82-1186-4a06-a48b-0edff51a4f17",
"name": "Setup",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
0,
-370
],
"parameters": {
"content": "## Instagram Profile Scraper - Bio & Posts\n\nSource: [dataspryva/instagram-profile-scraper-bio-and-posts](https://apify.com/dataspryva/instagram-profile-scraper-bio-and-posts) on Apify.\n\n1. In **Run Apify Actor**, create a Header Auth credential: name `Authorization`, value `Bearer YOUR_APIFY_TOKEN` with your token.\n2. Click **Execute workflow**. Each record arrives as one n8n item.\n3. Edit the JSON body of **Run Apify Actor** to change the input.\n\nGenerated by recipeforagents.com. Validated, not executed: runs are billed to your Apify account.",
"height": 340,
"width": 460,
"color": 6
}
}
],
"connections": {
"Run by hand": {
"main": [
[
{
"node": "Run Apify Actor",
"type": "main",
"index": 0
}
]
]
},
"Every day": {
"main": [
[
{
"node": "Run Apify Actor",
"type": "main",
"index": 0
}
]
]
}
},
"pinData": {},
"active": false,
"settings": {
"executionOrder": "v1"
},
"meta": {
"templateCredsSetupCompleted": false
},
"tags": []
} Import with Workflows, Import from file, or paste into the canvas. Credentials are not included: you select them after import.
All 7 destination variants pass the same checks at build time. Built-in nodes only, at versions n8n has shipped since 1.80: they import on n8n Cloud and older self-hosted instances without community nodes. Prefer Apify's own node? The verified community node @apify/n8n-nodes-apify runs the same Actor with OAuth sign-in on n8n Cloud.
Runs longer than 5 minutes? The synchronous endpoint answers HTTP 408 after 300 seconds. The long-run variant starts the run, checks it every minute until it ends, then reads its dataset (HTTP Request, If and Stop and Error nodes only).
Download the long-run workflow11 of 11 checks pass, not executed
Call it from code
Run the Actor from a script or your own agent framework with the Apify API. The call waits for the run to finish and returns the records. The input is the example below.
curl
curl -X POST "https://api.apify.com/v2/actors/dataspryva~instagram-profile-scraper-bio-and-posts/run-sync-get-dataset-items" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"usernames":["instagram"],"maxPosts":3}' Install: pip install "apify-client>=3"
Python
import os
from apify_client import ApifyClient
client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
"usernames": [
"instagram",
],
"maxPosts": 3,
}
run = client.actor("dataspryva/instagram-profile-scraper-bio-and-posts").call(run_input=run_input)
if run is None:
raise RuntimeError("The Actor run could not be started")
print(run.status, "dataset", run.default_dataset_id)
for item in client.dataset(run.default_dataset_id).iterate_items():
print(item) Install: npm install apify-client
JavaScript
import { ApifyClient } from "apify-client";
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const input = {
"usernames": [
"instagram"
],
"maxPosts": 3
};
const run = await client.actor("dataspryva/instagram-profile-scraper-bio-and-posts").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, items[0]); Example input
These values come from the Actor's Store prefill and required defaults. Change the search, URL or limit before your first run.
Actor inputinput.json
{
"usernames": [
"instagram"
],
"maxPosts": 3
} | Field | Type | What it does |
|---|---|---|
usernames required | array | Instagram profiles to scrape. Each entry can be a username (with or without @) or a profile link such as https://www.instagram.com/natgeo/. Each profile is scraped in turn. Example: 'instagram', '@instagram' or… |
maxPosts | integer | Maximum number of posts to extract per profile (after the date and pinned-post filters below). Set to 0 to only extract profile data without posts. Public profiles need no sign-in, however many posts you ask for. |
3 more optional fields on the Store input tab.
What your agent receives
Each run returns a list of records. The Actor publishes 30 fields, starting with post_url, shortcode, post_id, username.
| Field | What it holds | Format |
|---|---|---|
post_url | Post URL | text |
shortcode | Instagram shortcode identifying the post | string |
post_id | Internal Instagram media id of the post | string |
status | Status | text |
username | Username | text |
author_meta | Full profile data of the scraped account | object |
caption | Caption | text |
hashtags | Hashtags extracted from the caption | array |
mentions | @mentions extracted from the caption | array |
tagged_users | Usernames tagged in the post | array |
20 more fields
| Field | What it holds | Format |
|---|---|---|
collaborators | Usernames listed as co-authors of the post | array |
caption_is_edited | Whether the caption was edited after posting | boolean |
pub_date | Published | text |
media_type | Type | text |
media_count | Media Count | number |
thumbnail_url | Thumbnail | text |
media_items | Every image/video in the post, in order, with per-item url/dimensions | array |
accessibility_caption | Instagram's auto-generated alt-text description of the media | string |
like_count | Likes | number |
comment_count | Comments | number |
likes_hidden | Whether the author hid the like count | boolean |
comments_disabled | Whether commenting is disabled on the post | boolean |
location | Tagged location, when present | object |
music | Music/audio attribution, when present (reels) | object |
scraped_at | ISO 8601 datetime when this record was scraped | string |
author_meta.full_name | Name | text |
author_meta.followers_count | Followers | number |
author_meta.is_verified | Verified | boolean |
author_meta.is_business | Business | boolean |
author_meta.category |
Agent skill
A SKILL.md in the open Agent Skills format. It teaches Claude Code, Codex and other skill-aware agents when to call this Actor, how to build the input and how to read the result, using the API directly.
SKILL.mdinstagram-profile-scraper-bio-and-posts/SKILL.md
---
name: instagram-profile-scraper-bio-and-posts
description: "Scrape public Instagram profiles from a list of usernames: bio, followers, following, post count, verified badge and bio links. Add recent posts with captions, hashtags, likes and comments. Export to Excel, CSV or JSON. Runs the Apify Actor dataspryva/instagram-profile-scraper-bio-and-posts. Use when the user needs Instagram data with fields such as post_url, shortcode, post_id, status, username, author_meta and an Apify token is available."
compatibility: "Needs network access, curl, and an APIFY_TOKEN environment variable. Runs are billed to the token owner's Apify account."
metadata:
actor: "dataspryva/instagram-profile-scraper-bio-and-posts"
store-url: "https://apify.com/dataspryva/instagram-profile-scraper-bio-and-posts"
---
# Instagram Profile Scraper - Bio & Posts
Use this skill to fetch Instagram data with the Apify Actor `dataspryva/instagram-profile-scraper-bio-and-posts` and work with the returned rows.
## Before running
1. Check that `APIFY_TOKEN` is set in the environment. Never print it or write it to a file.
2. Build `input.json` from the user's request using the fields below. Keep limits small for a first run.
3. Confirm the search terms or URLs with the user if the request is ambiguous.
## Input fields
| Field | Type | Meaning |
| --- | --- | --- |
| `usernames` | array, required | Instagram profiles to scrape. Each entry can be a username (with or without @) or a profile link such as https://www.instagram.com/natgeo/. Each profile is scraped in turn. Example: 'instagram', '@instagram' or 'https://www.instagram.com/instagram/'. |
| `maxPosts` | integer | Maximum number of posts to extract per profile (after the date and pinned-post filters below). Set to 0 to only extract profile data without posts. Public profiles need no sign-in, however many posts you ask for. |
Example `input.json` (the Actor's published prefill):
```json
{
"usernames": [
"instagram"
],
"maxPosts": 3
}
```
## Run
```bash
curl -sS -X POST "https://api.apify.com/v2/acts/dataspryva~instagram-profile-scraper-bio-and-posts/run-sync-get-dataset-items" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d @input.json > results.json
```
The call waits for the run to finish and returns the dataset items as a JSON array. If the run needs more than 300 seconds the API answers with HTTP 408; then start the run with `POST /v2/acts/dataspryva~instagram-profile-scraper-bio-and-posts/runs`, poll `GET /v2/actor-runs/{runId}` until `SUCCEEDED`, and read `GET /v2/datasets/{defaultDatasetId}/items`.
## Output
Each item is one record. Published fields include: `post_url`, `shortcode`, `post_id`, `status`, `username`, `author_meta`, `caption`, `hashtags`, `mentions`, `tagged_users`, `collaborators`, `caption_is_edited`, `pub_date`, `media_type`, `media_count`, `thumbnail_url`, `media_items`, `accessibility_caption`, `like_count`, `comment_count`.
Summarise what was found, cite the record URLs when present, and say how many items came back. Do not invent values for empty fields.
- Claude Code: save it as
~/.claude/skills/instagram-profile-scraper-bio-and-posts/SKILL.md, or.claude/skills/instagram-profile-scraper-bio-and-posts/SKILL.mdin a project. - Codex and other agents:
~/.agents/skills/instagram-profile-scraper-bio-and-posts/SKILL.md, or.agents/skills/instagram-profile-scraper-bio-and-posts/in a project. - Or let the skills CLI place it for your agent:
npx skills add https://recipeforagents.com --skill instagram-profile-scraper-bio-and-posts - Set
APIFY_TOKENin the agent's environment.
Good jobs for this Actor
- Build an account review sheet with username, author_meta.full_name, author_meta.followers_count and author_meta.is_verified.
- Group recent posts by hashtags and mentions while retaining caption and post_url for review.
- Flag posts with likes_hidden or comments_disabled before comparing like_count and comment_count.
Prompts to try
- Scrape @natgeo and @instagram using usernames, and return their recent captions, hashtags and post links.
- Use https://www.instagram.com/natgeo/ in usernames and list recent posts with publication dates, media types and engagement counts.
- Scrape @instagram with skipPinnedPosts enabled and show mentions, tagged users and collaborators from the returned posts.
Recipes with this Actor
Instagram posts to Google Sheets
Log the latest posts of the Instagram profiles you track in a Google Sheet, with captions, likes, comments and post…
InstagramGoogle SheetsInstagram posts to Slack
Post the latest posts of the Instagram profiles you watch to a Slack channel, with caption, likes and the post link.
InstagramSlack
Troubleshooting
Why does the client say Unauthorized or invalid token?
Every Apify Actor tool needs a signed-in Apify account. Reconnect the server so the OAuth sign-in runs again, or switch to the token variant: an Authorization: Bearer header with an API token from Apify Console, Settings, API and integrations. For a local server the token must be in the server's own env block, not only in your shell.
Source: Apify MCP server README
Why did my agent's tool list change after an update?
Without a tools parameter Apify's server loads its default tool set, which changes between releases. The URLs on this site pin the tools with ?tools=, so the agent always gets the same Actor tool plus fetch-actor-details. Apify's README gives the same advice for production.
Source: Apify MCP server README
What happens when the agent sends input the Actor rejects?
The server answers with the Actor's input schema, so the agent can fix the arguments and call again. The fetch-actor-details tool in every scoped URL lets it read that schema before the first call.
Source: Apify MCP server README
Questions
Do public profiles require Instagram cookies?
Public profiles can be scraped without signing in. Leave cookies empty for that use.
Can an agent limit which posts it retrieves?
Use maxPosts to limit posts per profile and newerThan to skip posts published before a chosen date. The post limit applies after the date and pinned-post filters.
How should hidden likes and disabled comments be handled?
The published schema includes likes_hidden and comments_disabled alongside like_count and comment_count. Use those flags to identify posts whose engagement counts need different treatment in a comparison.
How do I connect Instagram Profile Scraper - Bio & Posts to Claude?
In Claude Code run: claude mcp add --transport http instagram-profile-scraper-bio-and-posts "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts". In Claude Desktop or claude.ai add a custom connector with the URL https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/instagram-profile-scraper-bio-and-posts and sign in to Apify. The agent then gets one tool for this Actor plus a tool that reads its input schema.
What input does Instagram Profile Scraper - Bio & Posts need?
The published input schema requires usernames. The example on this page uses the Actor's own Store prefill.
What does Instagram Profile Scraper - Bio & Posts cost to run?
The Apify Store lists $0.70 per 1,000 results (pay per event) for this Actor, checked 2026-11-12. Runs are billed to the Apify account whose token or sign-in the agent uses; Apify platform usage can add to that.
Which tools does the MCP config give my agent?
6 tools: fetch-actor-details, get-actor-run, get-dataset-items, get-key-value-store-record, abort-actor-run, dataspryva--instagram-profile-scraper-bio-and-posts. Apify's MCP server listed them for this exact URL on 2026-11-11.
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