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  3. Xbbg MCP
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Xbbg MCP

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View RepositoryVisit Website

Local Bloomberg tools for xbbg users.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "xbbg-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "xbbg-mcp"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

xbbg banner

CI PyPI version Conda version npm version Python versions PyPI downloads npm downloads Discord

Links: Documentation Β· Quickstart Β· Configuration Β· Examples notebook Β· Contributing Β· Changelog


Latest release: xbbg==1.4.11 (release: notes)

This main branch is the Rust-powered v1 release. For the legacy pure-Python line, use release/0.x.

Important: xbbg is an independent open-source project. It is not affiliated with, endorsed by, sponsored by, or approved by Bloomberg Finance L.P. or its affiliates. Bloomberg, Bloomberg Terminal, B-PIPE, BQL, and related names are trademarks or service marks of their respective owners. xbbg does not grant access to Bloomberg services, data, software, licenses, credentials, or entitlements; users must obtain and use those separately under their own Bloomberg agreements and applicable policies.

Contents

  • What is xbbg?
  • Why xbbg?
  • Installation
  • Quickstart
  • JavaScript and Node
  • Configuration and engines
  • Common API surface
  • Entitlement IDs
  • Output backends
  • Async usage
  • Subscriptions: raw, tick mode, and all fields
  • MCP server
  • Troubleshooting
  • Development
  • Project links

What is xbbg?

xbbg is a Bloomberg client with Python as the primary surface and companion JavaScript/Node bindings, all backed by a shared Rust engine for request execution, response parsing, Arrow-shaped data movement, async workers, typed errors, and diagnostics.

Use xbbg when you already have Bloomberg access and want higher-level helpers for common request patterns, plus an escape hatch for lower-level Bloomberg service requests.

Core scope:

  • request helpers for BDP, BDS, BDH, intraday bars, ticks, BQL, BEQS, BSRCH, BQR, BTA, YAS, and related analytics
  • local Bloomberg Desktop API / DAPI by default
  • configuration for managed Bloomberg environments, including B-PIPE/SAPI, ZFP leased lines, TLS, failover hosts, SOCKS5, and SDK logging
  • sync and async Python APIs backed by the same engine
  • output as Narwhals, native xbbg Arrow carriers, PyArrow, pandas, Polars, DuckDB, and other optional Narwhals-backed libraries
  • JavaScript/Node bindings in js-xbbg

Why xbbg?

xbbg's project goal is direct: be the most complete, technically advanced, and performance-focused open-source Bloomberg client for Python workflows, while staying independent of Bloomberg and requiring users to bring their own authorized Bloomberg access.

The short version: if all you need is a tiny one-off bdp() wrapper, several packages can work. xbbg is built for the path where that notebook later grows into intraday data, BQL, streaming, B-PIPE/SAPI, ZFP, async services, typed errors, diagnostics, and non-pandas data pipelines.

Capabilityxbbgraw blpapipdblp / blpbbg-fetchpolars-bloomberg
BDP/BDS/BDH helpersyesmanual SDK codeyesyespartial
Intraday bars and ticksyesmanual SDK codelimited / nonopartial
Streaming subscriptionsyesmanual SDK codenonono
BQL, BEQS, BSRCH, BQR, YAS, BTAbroad helper coveragemanual SDK codelimitedlimitedpartial
DAPI, SAPI/B-PIPE, ZFP, TLS, failover, SOCKS5configurable engine supportmanual SDK codelimitedlimitedlimited
Async worker pools and isolated subscription sessionsyesapplication-ownednonono
Rust request/parsing engine with Arrow-shaped outputyesnononono
Output backends beyond pandasNarwhals, native, PyArrow, pandas, Polars, DuckDBapplication-ownedpandas-firstpandas-firstPolars-first
Typed errors, diagnostics, field cache, testing helpersyesapplication-ownedlimitedlimitedlimited
Usable install footprint (Windows x64, Python 3.14)xbbg 1.3.0 + narwhals 2.22.1, no blpapi = 16.933 MiBblpapi 3.26.5.1 = 14.401 MiBpdblp 0.1.8 + pandas 3.0.3 + numpy 2.4.6 + blpapi 3.26.5.1 = 129.344 MiB / blp 0.0.4 + pandas 3.0.3 + numpy 2.4.6 + blpapi 3.26.5.1 = 129.530 MiBbbg-fetch 2.0.2 + pandas 3.0.3 + numpy 2.4.6 + blpapi 3.26.5.1 = 129.360 MiBpolars-bloomberg 0.6.0 + polars 1.41.2 + blpapi 3.26.5.1 = 197.296 MiB

Installation

Terminal
pip install xbbg

Conda users can install the conda-forge build:

cmd
conda install -c conda-forge xbbg

blpapi is not required as a Python dependency. xbbg only needs Bloomberg's shared runtime library (blpapi3_64.dll on Windows, libblpapi3_64.so on macOS/Linux), which can come from Bloomberg Terminal/DAPI, a managed Bloomberg C++ SDK install, or Bloomberg's official blpapi wheel. Installing the wheel is just the easiest discovery path for many users:

Terminal
pip install blpapi --index-url=https://blpapi.bloomberg.com/repository/releases/python/simple/

Supported Python versions: 3.10 through 3.14.

Requirements and notes:

  • You need an authorized Bloomberg environment: local Terminal/DAPI, SAPI/B-PIPE, or ZFP, depending on your setup.
  • If you build from source, stage the Bloomberg C++ SDK with bash ./scripts/sdktool.sh on macOS/Linux or .\\scripts\\sdktool.ps1 on Windows PowerShell.
  • If you manage the SDK yourself, set BLPAPI_ROOT or use xbbg.set_sdk_path(...).
  • On Windows Terminal installs, xbbg automatically probes DAPI runtime roots such as C:\blp\DAPI and C:\Program Files (x86)\Bloomberg\Blp\DAPI before requiring manual configuration.
  • Linux wheels are manylinux_2_28 (x86_64): any distro with glibc β‰₯ 2.28 works β€” RHEL/Alma/Rocky 8+, Debian 10+, Ubuntu 20.04+, Amazon Linux 2023.
  • Optional dataframe conversions are installed separately: xbbg[pyarrow], xbbg[pandas], xbbg[polars], or xbbg[duckdb].

Verify the install:

server.ts
import xbbg

print(xbbg.__version__)
print(xbbg.get_sdk_info())

Quickstart

server.ts
from xbbg import blp

# Reference data
prices = blp.bdp(["AAPL US Equity", "MSFT US Equity"], "PX_LAST")

# Historical data
hist = blp.bdh("SPX Index", "PX_LAST", "2024-01-01", "2024-12-31")

# Intraday bars
bars = blp.bdib("TSLA US Equity", dt="2024-01-15", interval=5)

Common request patterns:

server.ts
from xbbg import blp, ovr

# Multiple fields
info = blp.bdp("NVDA US Equity", ["Security_Name", "GICS_Sector_Name", "PX_LAST"])

# Bloomberg-style overrides
vwap = blp.bdp("AAPL US Equity", "Eqy_Weighted_Avg_Px", VWAP_Dt="20240115")
adj = blp.bdp("AAPL US Equity", "CRNCY_ADJ_PX_LAST", overrides=ovr(EQY_FUND_CRNCY="EUR"))
per_sec = blp.bdp(
    ["AAPL US Equity", "MSFT US Equity"],
    "CRNCY_ADJ_PX_LAST",
    overrides=ovr(
        {
            "EQY_FUND_CRNCY": "USD",
            "AAPL US Equity": ovr(EQY_FUND_CRNCY="EUR"),
            "MSFT US Equity": ovr(EQY_FUND_CRNCY="JPY"),
        }
    ),
)

# Bulk data
holders = blp.bds("AAPL US Equity", "DVD_Hist_All", DVD_Start_Dt="20240101")

# BQL
result = blp.bql("get(px_last) for('AAPL US Equity')")

# Field lookup
fields = blp.bflds(search_spec="vwap")

# Equity screening and constituents
screen = blp.beqs(screen="MyScreen", asof="2024-01-01")
members = blp.index_members("SPX Index", asof="2024-01-02")

# Workflow helpers
active = blp.active_futures("ESA Index", "2024-01-15")
surface = blp.vol_surface("SPX Index", start_date="2024-01-02", end_date="2024-01-05")
resolved = blp.resolve_isins(["US0378331005", "INVALIDISIN000"])

ETF NAV / iNAV workflows live in xbbg.ext and resolve Bloomberg's authoritative ETF_NAV_TICKER / ETF_INAV_TICKER relationships instead of guessing ticker suffixes:

server.ts
from xbbg import ext

# Relationship discovery: QQQ US Equity -> QQQNV Index / QXV Index,
# AT1 LN Equity -> null daily NAV / AT1IN Index (independently nullable)
rel = ext.etf_nav_relationships(["QQQ US Equity", "AT1 LN Equity"])

# Daily NAV/iNAV history: mapped Index targets price with PX_LAST; AT1's
# missing daily NAV falls back to the fund's FUND_NET_ASSET_VAL β€” see the
# nav_source_ticker / nav_source_field columns on every row
hist = ext.etf_nav_history(
    ["QQQ US Equity", "AT1 LN Equity"],
    start_date="2026-06-01",
    end_date="2026-07-01",
)

Read the full README β†’View source on GitHub β†’

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Frequently Asked Questions about Xbbg MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "xbbg-mcp": { "command": "npx", "args": ["-y", "xbbg MCP"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
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24Quality signal: Emerging Β· 24/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools9/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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