Bitrix24 BI-connector protocol

This skill captures the HTTP protocol for the Bitrix24 BI-analytics connector — the API that powers Power BI / Google Data Studio integrations and any custom client that reads CRM data from a Bitrix24 portal. Use it when constructing requests, helping users count/filter CRM entities, or implementing a BI client.

Endpoints overview

All three endpoints live on the client's Bitrix24 portal. Every request is HTTP POST and every body MUST include a key field — the client's bi-token. Only the path and query string vary: gds.php for metadata (list/describe), pbi.php for actual data rows.

Where the bi-token comes from: the BI-analytics key-management page of the client's own Bitrix24 portal (path varies by portal locale; on a fresh portal navigate via CRM → Analytics → BI-analytics → BI-analytics settings → Key management, or open {portal}/biconnector/key_list.php directly). Always ask the user for their own portal URL — never hardcode a reference portal (e.g. smith.bitrix24.com from sample docs) in production code.

Endpoint 1 — list tables

POST {portal}/bitrix/tools/biconnector/gds.php?show_tables

Body:

{"key": "<bi-token>"}

Returns [[table_name, table_description], ...].

Endpoint 2 — describe a table's columns

POST {portal}/bitrix/tools/biconnector/gds.php?desc&table=<table_name>

Body:

{"key": "<bi-token>"}

Returns an array of column objects. Key fields per column:

• CONCEPT_TYPE — DIMENSION or METRIC. METRICs are typically aggregated and grouped by DIMENSIONs — preserve this distinction in any UI or query-builder code.
• ID — the identifier to use when referencing the column in subsequent requests (this is the name you pass in endpoint 3's fields).
• NAME — human-readable label.
• TYPE — data type (e.g. NUMBER, STRING, YEAR_MONTH_DAY_SECOND).
• AGGREGATION_TYPE, GROUP_KEY, GROUP_CONCAT, GROUP_COUNT, IS_VALUE_SPLITABLE — aggregation/grouping hints, often null.

Endpoint 3 — fetch table rows

POST {portal}/bitrix/tools/biconnector/pbi.php?table=<table_name>

Body:

{"key": "<bi-token>", "fields": [{"name": "<column_id>"}, ...]}

fields lists which columns to return; use the ID values from endpoint 2. Response is a 2D array where the first row is the header (column names in request order) and the rest are data rows aligned to that header. Empty cells come back as null or "" — don't treat absence as an error.

Silent-failure traps

The BI-connector has several behaviours where bad requests succeed with HTTP 200 but return misleading results. These cause real bugs because they look indistinguishable from "no data matched":

Unknown fields are silently dropped. If you request fields that don't exist on the table, the API silently drops them. If all requested fields are unknown, you get {"error":"EMPTY_SELECT_FIELDS_LIST"} with HTTP 200 — it does not name which field was wrong. Always cross-check field IDs against endpoint 2 before querying.

Unknown operators are silently ignored. Spelling an operator wrong, or guessing one that doesn't exist (e.g. IS_NOT_NULL, STARTS_WITH), causes the server to return the unfiltered set — which looks like a successful query. Never assume an operator exists without testing it on a column with known distribution. Confirmed operators are listed below; treat everything else as unproven.

Request bodies must be UTF-8 encoded. If a filter value or URL parameter contains any non-ASCII character (in dimensionsFilters values, in a non-Latin table name, etc.), the body MUST be sent as UTF-8 bytes. A mismatched encoding does NOT produce an error — the API returns an empty result set (Rows: 0), which is indistinguishable from a legitimate "no matches". PowerShell Invoke-RestMethod -Body $stringWithNonAscii is a known offender on Windows because its default body encoding is not UTF-8: pass [Text.Encoding]::UTF8.GetBytes($json) and Content-Type: application/json; charset=utf-8 instead. In any language, set the HTTP client's body encoding to UTF-8 explicitly when sending non-ASCII filter values.

Date-range filtering

Add dateRange and optionally configParams.timeFilterColumn to the pbi.php body:

{ "key": "bi-token", "dateRange": {"startDate": "2018-07-19", "endDate": "2018-08-02"}, "configParams": {"timeFilterColumn": "DATE_CREATE"}, "fields": [{"name": "DATE_CREATE"}, {"name": "STATUS_SEMANTIC_ID"}] } 

• startDate is treated as 00:00:00 of that day; endDate as 23:59:59.999 (inclusive).
• For a single day, set startDate = endDate.
• timeFilterColumn is the column ID to filter on. If omitted, the API uses the first date/datetime column in the table — usually safe but explicit is better.

Rule — always filter: always pass a dateRange when calling pbi.php, even if the user didn't ask. Without it, unfiltered tables can return thousands or millions of rows on real portals. Default to "last 3 months" (endDate = today, startDate = today − 90 days) unless the user specifies otherwise. The metadata endpoints (show_tables, desc) don't accept dateRange — only pbi.php does. Exception: if you're using dimensionsFilters (below) and it sufficiently narrows the result (e.g. filtering by a specific ID), dateRange is optional.

Predicate filtering with dimensionsFilters

Add to the pbi.php body a key dimensionsFilters whose value is an array of arrays of condition objects. Outer arrays are joined by AND; inner conditions within one array are joined by OR. Any number of inner conditions and any number of outer groups is allowed.

{ "key": "bi-token", "fields": [{"name": "ID"}, {"name": "CREATED_BY_ID"}], "dimensionsFilters": [ [ {"fieldName": "ID", "values": ["2"], "type": "INCLUDE", "operator": "EQUALS"}, {"fieldName": "ID", "values": ["12706"], "type": "INCLUDE", "operator": "EQUALS"} ], [ {"fieldName": "CREATED_BY_ID", "values": ["1"], "type": "INCLUDE", "operator": "EQUALS"} ] ] } 

Above: (ID=2 OR ID=12706) AND CREATED_BY_ID=1.

Condition object fields

• fieldName — column ID from endpoint 2.
• values — always a list of strings, even for numeric columns (e.g. "1", not 1).
• type — "INCLUDE" (apply the operator) or "EXCLUDE" (invert it). EXCLUDE works as a universal negator on top of any operator: EXCLUDE + EQUALS = "not equal", EXCLUDE + CONTAINS = "doesn't contain", EXCLUDE + IN_LIST = "not in list", EXCLUDE + IS_NULL = "not null" (the stand-in for the missing IS_NOT_NULL).
• operator — confirmed values:
• "EQUALS" — exact match; values is a single-element list, e.g. ["1"].
• "CONTAINS" — substring match, e.g. {"fieldName":"TITLE","values":["CRM:"],"operator":"CONTAINS"}.
• "IN_LIST" — field value is any of the listed strings, e.g. {"fieldName":"ID","values":["1","2"],"operator":"IN_LIST"}. Prefer this over OR-ing multiple EQUALS conditions for the same field — cleaner and one condition object instead of N.
• "IS_NULL" — null check; values MUST be an empty list ([]). For non-null, use EXCLUDE + IS_NULL (there is no standalone IS_NOT_NULL operator — the server silently ignores it and returns all rows unfiltered). Caveat: the desc metadata does NOT expose which fields are nullable, so there's no way to verify at runtime. Only use this when you already know from data inspection or domain context that the field can hold null.
• "BETWEEN" — value in range, both endpoints inclusive. values MUST be a 2-element list [low, high] (as strings, like all other operators). Behaviour on non-numeric columns is unspecified — treat it as numeric/date-only and test before applying to strings.
• "NUMERIC_GREATER_THAN" / "NUMERIC_GREATER_THAN_OR_EQUAL" / "NUMERIC_LESS_THAN" / "NUMERIC_LESS_THAN_OR_EQUAL" — >, >=, <, <=. Single-element values, e.g. ["2"]. Behaviour on non-numeric columns is unspecified — use on numeric/date columns and verify before applying to strings.
• Anything else (e.g. STARTS_WITH, ENDS_WITH, REGEX) is unproven. Per "Silent-failure traps" above, an unknown operator returns the full unfiltered table — which looks like a wide-open match. Test on a known-distribution column before relying on it.

Useful pattern — fetch a single row by ID

"dimensionsFilters": [[{"fieldName":"ID","values":["19244"],"type":"INCLUDE","operator":"EQUALS"}]]

Success/failure semantics in CRM entities

Bitrix24 uses a one-letter "semantic" code to indicate where an entity sits in its lifecycle. Same codes, different field names across entities — easy to mix up:

• P — in progress (non-terminal)
• S — successful terminal state
• F — failed terminal state

To count "successful" leads or deals, filter on the _SEMANTIC_ID field equal to S. To count "completed" (any terminal state), include both S and F. The text-label variants (STATUS_SEMANTIC, STAGE_SEMANTIC) come back as localized strings in the portal's UI language — use them for display, not for filtering. The single-letter _ID codes are stable across locales and should always be the key you filter on. Smart-process entities (crm_dynamic_items_*) likely follow the deal convention (stages) — verify via endpoint 2 before assuming.

Non-CRM entities like task may use a completely different schema (e.g. a raw STATUS column holding a localized human-readable string, with no semantic code at all). Always check endpoint 2 before generalizing — don't assume STATUS_SEMANTIC_ID exists outside the CRM tables documented above.

Credential handling

The bi-token is a credential. Treat it as you would any API key: never log it, never commit it to source control, never echo it back in error messages or stack traces. When building configuration scaffolding for an implementation, read the token from an environment variable or a gitignored config file — never a hardcoded constant in committed code.

Adresse de la requête :

 POST https://example.bitrix24.fr/bitrix/tools/biconnector/gds.php?show_tables 

Corps de la requête :

 { "key": "votre_clé_BI_Analytics" } 

Exemple de réponse :

 [ ["crm_lead", "Prospects"], ["crm_deal", "Transactions"], ["task", "Tâches"] ] 

Adresse de la requête :

 POST https://example.bitrix24.fr/bitrix/tools/biconnector/gds.php?desc&table=crm_lead 

Corps de la requête :

 { "key": "votre_clé_BI_Analytics" } 

Exemple de réponse :

 [ { "ID": "ID", "NAME": "Identifiant unique", "TYPE": "NUMBER" }, { "ID": "TITLE", "NAME": "Nom du prospect", "TYPE": "STRING" }, { "ID": "DATE_CREATE", "NAME": "Date de création", "TYPE": "DATETIME" }, { "ID": "STATUS_ID", "NAME": "Statut", "TYPE": "STRING" }, { "ID": "ASSIGNED_BY_ID", "NAME": "Responsable", "TYPE": "NUMBER" } ] 

Adresse de la requête :

 POST https://example.bitrix24.fr/bitrix/tools/biconnector/pbi.php?table=crm_lead 

Corps de la requête :

 { "key": "votre_clé_BI_Analytics", "fields": [ { "name": "ID" }, { "name": "TITLE" }, { "name": "DATE_CREATE" }, { "name": "STATUS_ID" }, { "name": "ASSIGNED_BY_ID" } ] } 

Exemple de réponse :

 [ ["ID", "TITLE", "DATE_CREATE", "STATUS_ID", "ASSIGNED_BY_ID"], ["125", "Demande de consultation", "2026-05-12 10:15:32", "NEW", "17"], ["126", "Commande d'équipement", "2026-05-13 14:42:10", "IN_PROCESS", "21"] ]