LinkedIn MCP Server

A standalone Python MCP server that exposes narrow, typed LinkedIn capabilities through the visible LinkedIn web UI.

[!IMPORTANT] This is an unofficial, beta project. It is not affiliated with, endorsed by, or sponsored by LinkedIn. LinkedIn is a trademark of LinkedIn Corporation. Visible-UI automation can stop working when LinkedIn changes its interface and may cause checkpoints, restrictions, or other account consequences. You are responsible for complying with applicable terms, laws, consent requirements, and organizational policies. Do not use this project for spam, deceptive activity, high-volume extraction, or bypassing access controls.

This repository is the LinkedIn harness, not an agent runtime. LangGraph, schedulers, ranking, memory, and natural-language planning belong in clients that call this server. Agents never receive cookies, arbitrary browser control, generic navigation, JavaScript execution, or unrestricted network access.

Version 0.15.0 has no database, migration, Docker-service, keyring, or application-state dependency. It uses one local Playwright Chromium profile to preserve the LinkedIn login and keeps capability execution state only for the lifetime of one server process.

Runtime model

LangGraph / Codex / another MCP client
                  |
          stdio or loopback HTTP
                  |
          typed MCP capabilities
                  |
      bounded asyncio.Queue (one worker)
                  |
     policy -> executor -> page objects
                  |
    one persistent Playwright context
                  |
       visible linkedin.com surfaces

The server owns:

• official MCP Python SDK transport and typed Pydantic contracts;
• one bounded in-process queue and one capability worker;
• one account-scoped persistent Playwright Chromium context;
• internal navigation pacing and per-operation safety bounds;
• exact-host, surface, scope, and effect authorization;
• visible page extraction and field-level evidence;
• expiring, filter-bound continuation cursors for collection reads;
• immutable prepare/confirm/execute envelopes for writes;
• process-local request replay, evidence, action drafts, and idempotency.

It has no dependency on LangGraph, Temporal, startup-scanner, PostgreSQL, RabbitMQ, Redis, or another LinkedIn MCP implementation.

What survives a restart

Data	Location	Lifetime
LinkedIn cookies and browser preferences	local Chromium profile	across restarts
Managed Chromium binaries	local Playwright browser cache	across package environments
Explicit post/message assets	configured local asset directory	user managed
Calls and request replay	memory	current process only
Evidence resources	memory	current process only
Action drafts and attempts	memory	current process only
Execution idempotency keys	memory	current process only
Queue and pacing history	memory	current process only
Collection cursors, seen identities, and invitation snapshots	memory	current process only

The browser profile is sensitive authentication material. Its directory is created with owner-only permissions on supported POSIX systems. Never commit, copy, log, or share it.

Privacy Policy

This is local software with no maintainer-operated backend, analytics, advertising, or telemetry. It processes visible LinkedIn content, operation evidence, approved write payloads, and explicitly referenced local assets only to serve the MCP client that invoked it. LinkedIn receives visible-UI requests and confirmed write content; the invoking MCP client receives tool results and may retain them under its own policy. The project does not sell personal data or transmit LinkedIn content, cookies, credentials, messages, or assets to the maintainer.

Operation state is retained only in process memory. The local Chromium profile persists until the operator signs out or deletes it, and the configured asset directory remains user managed. Stop the server and remove those directories to delete persistent local data. Privacy questions can be filed in the public issue tracker without sensitive content or sent to prakharagarwal3031@gmail.com.

The complete policy covers data collection, use, local storage, third-party sharing, retention, deletion, and contact details in PRIVACY.md. LinkedIn separately processes activity under the LinkedIn Privacy Policy.

Because operation state is intentionally ephemeral:

• read retries deduplicate only while the same server process is alive;
• linkedin://sources/{source_id} must be read before that process exits;
• a prepare and its matching execute call must use the same process;
• after a hard process interruption during a write, inspect LinkedIn's visible state before preparing any new action. Never blindly retry the old execute request.

LangGraph should checkpoint workflow history, cross-run deduplication, notifications, rankings, and conversations outside this server.

MCP surface

MCP primitive	Purpose
linkedin.server.status	Non-secret runtime metadata
linkedin.capabilities.list	Installed capabilities and policy status
linkedin.session.status	Browser setup, profile, authentication, and pause state
linkedin.jobs.search	Cursor-paged current Jobs search with optional keywords, Any time by default, and every current account-visible filter
linkedin.jobs.get	Expanded JD, header metadata, application method, and hiring team for a numeric job ID
linkedin.people.search	Bounded People search with every current account-visible filter
linkedin.people.get	Selected or all visible member-profile sections
linkedin.companies.search	Cursor-paged Company search with keywords and every current native filter: headquarters, industry, all eight size buckets, job listings, and first-degree connection presence
linkedin.companies.get	Exact Company Overview plus About, including all visible structured About fields and field evidence
linkedin.posts.search	Post search with every current visible filter, including live videos, followed authors, and Author Keywords
linkedin.posts.get	Exact post read with fully expanded text, typed current media/link/poll variants, engagement and visibility, field evidence, completeness coverage, and bounded repost-original resolution
linkedin.posts.comments.list	Top-level comments and nested replies
linkedin.posts.create.prepare / .execute	Nine current personal composer modes: text/link, edited images, video, document, poll, celebration, event, existing-job hiring, and expert request; plus audience/group, comment control, brand partnership, eligible collaborators, and scheduling
linkedin.posts.comment.prepare / .execute	Top-level comment or exact-thread reply with text/emoji/link, exact mentions, one photo, or one exact GIF
linkedin.posts.reaction.prepare / .execute	Set, change, remove, or no-op any current post/comment reaction: Like, Celebrate, Support, Love, Insightful, or Funny
linkedin.invitations.list	Exact sent view or deduplicated union of every current received invitation view
linkedin.connections.list	Cursor-page and sort the existing first-degree connection inventory
linkedin.connections.search	Search established first-degree connections with first-degree enforced by the server
linkedin.invitations.send.prepare / .execute	Connection invitation with optional note
linkedin.invitations.accept.prepare / .execute	Accept an exact received invitation
linkedin.invitations.ignore.prepare / .execute	Ignore an exact received connection request
linkedin.messaging.search	Cursor-paged recipient/message-keyword search across Focused, Other, Archived, or Spam with exactly one optional Jobs, Unread, Connections, InMail, or Starred filter
linkedin.messaging.conversation.get	Bounded reverse-virtualized one-to-one history with incoming/outgoing messages, visible attachments, replies, edits, reactions, and explicit completeness
linkedin.messaging.message.prepare / .execute	Exact-recipient text/emoji, current desktop image/file, exact KLIPY GIF, or exact-message reply with hash-locked confirmation and visible postconditions
linkedin://sources/{source_id}	Evidence captured by the current process

Every operation accepts a caller-owned context_id and request_id. Direct detail reads do not require a prior search. The server constructs bounded, canonical LinkedIn targets from validated job IDs, profile slugs, company slugs, post references, comment references, and conversation references.

Collection pagination

Every LinkedIn search or list tool accepts page_size (1–100) and an optional opaque cursor. Omit cursor for the first page, then copy pagination.next_cursor into the next call with a new request_id. A terminal page has pagination.has_more=false.

Cursors are process-local, single-use, expire after 15 minutes by default, and are bound to the account, capability, and semantic filters that created them. Changing page_size between pages is allowed; changing the search target, query, sort, direction, or filters is rejected as invalid_cursor. The server rescans a bounded live prefix and removes stable identities already returned, so consistency=live_deduplicated prevents duplicates but does not claim a frozen LinkedIn snapshot. truncated=true means an internal safety or cursor state bound ended the scan and no further cursor is issued.

linkedin.invitations.list uses a stronger contract. A single-filter call captures and exactly reconciles that view against LinkedIn's visible count. Received all is server-defined because the latest UI has no reliable All control: it reconciles Focused, Other, Verified, Mutual Connections, Your Company, and Your School separately, then deduplicates their stable invitation identities. Coverage reports the per-view counts, their membership sum, the overlap removed, and the exact unique snapshot count. Continuations slice that immutable process-local snapshot without reopening LinkedIn and report consistency=captured_snapshot. A quiet list, physical bottom, loader state, or end message can never substitute for count reconciliation.

For asynchronously rendered feeds, the server compares raw visible card identities independently of parsing. A quiet polling window is not treated as the end of a list. Completion requires either an explicit visible empty/end state or, for LinkedIn member lists, three unchanged probes at the physical bottom of the visible scroll container with no loader or tail control. When LinkedIn exposes an exact count for another selected member collection, such as N connections, neither an early end message nor a stable bottom is accepted until that visible inventory has rendered. Invitation recommendations are excluded from the invitation snapshot and reported separately. Exhaustion of a private traversal bound returns an honest truncated result.

The paginated tools are Jobs, People, Company, post, broad Connections, and message search; post comments; and invitation and first-degree connection lists. Exact single-resource reads remain non-cursor operations. Company-authored posts use linkedin.posts.search with author_company_* filters; company employees use linkedin.people.search with current_company_* filters. For transition compatibility, compatible non-v2 collection tools still accept the older max_results or max_comments aliases for page_size.

See the visible-feature matrix for exact filters, selectors, payloads, exclusions, capability versions, and visible postconditions.

Package and local setup

Prerequisites are Python 3.12 or 3.13 and uv. Docker is not required.

Run the published PyPI package without a permanent installation:

uvx --from linkedin-mcp-local linkedin-mcp setup

Clone and validate a source checkout:

git clone https://github.com/prakharagarwal-dev/linkedin-mcp-server.git
cd linkedin-mcp-server
uv sync --frozen --all-groups
uv run linkedin-mcp setup

Chromium installs automatically into the per-user application-data cache when the server first needs it. To install it explicitly:

uv run linkedin-mcp setup

The project builds as a normal wheel:

uv build
uvx --from ./dist/linkedin_mcp_local-0.15.0-py3-none-any.whl \
  linkedin-mcp doctor

The wheel does not contain Chromium or a LinkedIn session. On first use, the installed CLI downloads the matching official Playwright Chromium revision to the shared user cache. A later wheel or uvx environment reuses that cache.

First LinkedIn login

Either start the MCP server or run login explicitly from the published package:

uvx --from linkedin-mcp-local linkedin-mcp login
uvx --from linkedin-mcp-local linkedin-mcp doctor

From a source checkout, use:

uv run linkedin-mcp login
uv run linkedin-mcp doctor

The login command:

1. ensures the matching official Playwright Chromium revision is installed;
2. opens a headed browser with the persistent LinkedIn MCP profile;
3. selects LinkedIn's visible Keep me signed in control when available;
4. waits for the user to complete LinkedIn login, MFA, or a checkpoint;
5. requires a persistent LinkedIn session cookie and departure from login surfaces;
6. closes Chromium normally, then reopens the exact profile in the configured headed or headless mode; and
7. verifies the authenticated LinkedIn feed before reporting success.

The server never asks for or stores a LinkedIn password itself. Later starts reuse and validate the same profile. Expired authentication can open the same human login flow. Restriction-shaped pages pause work for operator attention.

With AUTO_LOGIN_ON_START=true, Chromium setup and login run in background tasks, so the MCP handshake itself does not wait for a download or human interaction.

Run as an MCP server

For a local client, stdio is the smallest transport:

uv run linkedin-mcp serve --transport stdio

For several local clients sharing one worker, browser, profile, and pacing state:

uv run linkedin-mcp serve --transport streamable-http

The HTTP endpoint is http://127.0.0.1:8000/mcp by default. Non-loopback binds are rejected because this release does not implement HTTP authentication.

One account lock prevents two server processes from concurrently owning the same configured runtime lock. Use one shared Streamable HTTP process if multiple local agents need simultaneous access.

Codex configuration

Use the published package from any repository:

[mcp_servers.linkedin]
command = "uvx"
args = [
  "--from",
  "linkedin-mcp-local==0.15.0",
  "linkedin-mcp",
  "serve",
  "--transport",
  "stdio",
]
startup_timeout_sec = 30
tool_timeout_sec = 900

For contributors, this source-checkout configuration does not depend on an activated virtual environment:

[mcp_servers.linkedin]
command = "uv"
args = [
  "run",
  "--project",
  "/absolute/path/to/linkedin-mcp-server",
  "linkedin-mcp",
  "serve",
  "--transport",
  "stdio",
]
startup_timeout_sec = 30
tool_timeout_sec = 900

An installed-wheel configuration can point command directly at the installed linkedin-mcp executable. Both forms reuse the same default browser profile and browser cache for the operating-system user.

Account-changing actions

Writes are separate from reads and use:

prepare visible target and payload
  -> action_id + payload_hash + exact approval_preview
  -> MCP client displays native destructive-tool confirmation
  -> execute validates the unchanged in-memory draft
  -> browser performs one final action
  -> visible postcondition is verified | failed | uncertain

Prepare tools do not change LinkedIn. Execute tools are marked destructive and require the exact action_id, SHA-256 payload_hash, approval_preview, and a new execution idempotency_key. An annotation asks the MCP client to confirm; it does not grant a server scope or bypass runtime authorization.

Connection invite preparation opens and validates LinkedIn's current confirmation dialog, including the visible 0/200 personalized-note counter, without invoking Send. Accept and ignore preparation resolve the exact member profile and require the current, paired Accept … request to connect and Ignore … request to connect controls. Their execute tools re-open that same profile immediately before the click and verify the terminal state on a fresh exact-profile read.

Enable only the required surfaces, scopes, and effects. A trusted MCP client must prompt the user for each execute tool. If the user denies the client prompt, the client must not call the server.

An execute call is never automatically retried after an uncertain result. With this database-free design, a hard process exit also erases the attempt record; visible LinkedIn state must be inspected before any follow-up.

Configuration

All environment settings use the LINKEDIN_MCP_ prefix.

Variable	Default	Meaning
ACCOUNT_ID	personal	One configured LinkedIn account
BROWSER_PROFILE_PATH	per-user app data	Persistent LinkedIn Chromium profile
BROWSER_CACHE_PATH	native Playwright cache	Managed Playwright browser cache
BROWSER_AUTO_INSTALL	true	Install the matching Chromium revision when needed
BROWSER_INSTALL_TIMEOUT_SECONDS	600	Browser installation bound
AUTO_LOGIN_ON_START	true	Validate/recover login in the background
ALLOWED_HOSTS	exact LinkedIn hosts	Navigation allowlist
ALLOWED_SURFACES	Jobs and People reads	Authorized LinkedIn UI surfaces
ALLOWED_SCOPES	Jobs and People reads	Authorized named capabilities
ALLOWED_EFFECTS	read	read, prepare, and/or write
QUEUE_CAPACITY	100	Maximum waiting local capability calls
MINIMUM_NAVIGATION_INTERVAL_SECONDS	2	Internal pacing interval
PAGINATION_CURSOR_TTL_SECONDS	900	Lifetime of an idle continuation cursor
PAGINATION_MAX_ACTIVE_CURSORS	64	Maximum process-local continuation states
PAGINATION_MAX_SEEN_ITEMS_PER_CURSOR	5000	Stable-identity memory bound per scan
ACTION_DRAFT_TTL_SECONDS	86400	Maximum in-process unexecuted draft age
ASSET_ROOT_PATH	per-user app data	Allowed local files for posts/comments/messages
RUNTIME_LOCK_PATH	per-user app data	Single-account process lock
BROWSER_HEADLESS	true	Capability browser mode; login remains headed
BROWSER_TIMEOUT_SECONDS	20	Browser operation timeout
LOGIN_TIMEOUT_SECONDS	900	Human login bound
TRANSPORT	stdio	stdio or streamable-http
HTTP_HOST / HTTP_PORT	127.0.0.1:8000	Loopback HTTP listener

Page and scroll traversal, member-profile section, comment-expansion, invitation, connection, and messaging safety bounds remain private server configuration. Callers control only the typed page_size and opaque cursor, not browser traversal or pacing. See .env.example for every variable and read-only defaults.

Container image

Pull the signed multi-architecture image, or build it locally. It has no companion database:

docker pull ghcr.io/prakharagarwal-dev/linkedin-mcp-server:0.15.0
docker build -t linkedin-mcp-server:0.15.0 .

It runs as UID/GID 10001, includes Chromium, defaults to stdio, and stores the persistent browser profile and user assets under /data/linkedin-mcp. Mount that directory intentionally. Automatic headed login is disabled in the image; create and mount a profile through an environment that can display Chromium.

Verification

The default suite is the complete mock_verified acceptance gate. It blocks external network access and never contacts LinkedIn:

uv run ruff format --check .
uv run ruff check .
uv run pyright
uv run pytest
uv run pytest --cov=linkedin_mcp --cov-branch
uv build

The enforced branch-coverage floor is 85%; the current gate contains 436 offline tests. The repository contains no live LinkedIn tests.

Safety boundary

There is no generic click, selector, navigation, JavaScript, browser, SQL, or network tool. The server uses only visible LinkedIn UI through official Playwright APIs and exact configured hosts.

LinkedIn access pauses on authentication expiry, authwalls, checkpoints, restriction-shaped pages, permission failures, and invalid configuration. The project does not implement CAPTCHA bypass, proxy rotation, fingerprint spoofing, credential harvesting, stealth plugins, or private LinkedIn endpoints.

Company/Page publishing, auto-apply, referral semantics, groups, paid InMail, and other materially different effects require separate future typed contracts. Operators are responsible for using the server only with accounts and activity they are authorized to operate.

See Architecture, security design, testing and mock verification, visible-feature matrix, publishing and package identifiers, contributing guide, security policy, and changelog.