Provides real-time bridge metrics, transaction volumes, and token statistics for the Ethereum network.
Provides real-time bridge metrics, transaction volumes, and token statistics for the Optimism network.
Provides real-time bridge metrics, transaction volumes, and token statistics for the Polygon network.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Bridge Metrics MCP Show all bridges with their supported chains"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
An MCP server that provides real-time cross-chain bridge metrics, enabling AI agents to analyze liquidity, transaction flows, and performance across blockchain networks.
List Chains: Retrieve a list of all chain slugs from DeFiLlama, sorted by Total Value Locked (TVL) in descending order.
List Bridges: Fetch all bridges, optionally including chain breakdowns, sorted by 24-hour volume.
Historical Volumes: Get historical volume data for a bridge or chain, with dates formatted as YYYY-MM-DD HH:MM:SS.
Daily Token Stats: Retrieve 24-hour token volume breakdowns, including token ID, symbol, decimals, deposit/withdrawal amounts, and USD values, sorted by deposit USD value.
Bridge Transactions: Fetch transaction summaries for a specific bridge, with details like transaction hash, timestamp, and USD value.
Prompts: Includes example prompts for analyzing bridge volumes and comparing bridges based on metrics like weekly volume.
Related MCP server: RWA Pipe MCP Server
Python: Version 3.10 or higher.
uv: Package and virtual environment manager for Python (recommended for dependency management).
Clone the Repository:
git clone https://github.com/kukapay/bridge-metrics-mcp.git
cd bridge-metrics-mcpInstall dependencies:
uv syncInstall to Claude Desktop:
Install the server as a Claude Desktop application:
uv run mcp install main.py --name "Bridge Metrics"Configuration file as a reference:
{
"mcpServers": {
"Bridge Metrics": {
"command": "uv",
"args": [ "--directory", "/path/to/bridge-metrics-mcp", "run", "main.py" ]
}
}
} Replace /path/to/bridge-metrics-mcp with your actual installation path.
The server provides the following tools, accessible via JSON-RPC or natural language prompts in compatible clients:
list_chains:
Description: Lists all chain slugs from DeFiLlama, sorted by TVL.
Parameters: None.
Output: Table with columns Name, Gecko ID, Token Symbol, Chain ID, TVL.
list_bridges:
Description: Lists all bridges, sorted by 24-hour volume, with optional chain inclusion.
Parameters: include_chains (boolean, default False).
Output: Table with columns ID, Name, Display Name, Last 24h Volume, Chains.
get_historical_volumes:
Description: Fetches historical volumes for a chain or bridge, with dates formatted as YYYY-MM-DD HH:MM:SS.
Parameters: chain (string, required), bridge_id (integer, optional).
Output: Table with columns Date, Deposit USD, Withdraw USD, Deposit Txs, Withdraw Txs.
get_day_stats:
Description: Retrieves 24-hour token volume breakdowns, sorted by deposit USD value.
Parameters: timestamp (integer, required), chain (string, required), bridge_id (integer, optional).
Output: Table with columns Token ID, Symbol, Decimals, Deposit Amount, Deposit USD Value, Withdraw Amount, Withdraw USD Value.
get_transactions:
Description: Fetches transaction summaries for a bridge, sorted by timestamp.
Parameters: bridge_id (integer, required), start_timestamp, end_timestamp, source_chain, address, limit (all optional).
Output: Table with columns Tx Hash, Timestamp, Block, From, To, Token, Amount, Type, Chain, Bridge Name, USD Value.
Prompts:
analyze_bridge_volume: Analyzes volume data for a specific bridge.
compare_bridges: Compares two bridges based on a specified metric (e.g., weeklyVolume).
Below are example interactions using natural language prompts in a compatible MCP client, along with expected results.
Prompt:
List all chains available on DeFiLlama.Tool Called: list_chains
Result:
+----------------+-------------+---------------+-----------+-------------+
| Name | Gecko ID | Token Symbol | Chain ID | TVL |
+================+=============+===============+===========+=============+
| Ethereum | ethereum | ETH | 1 | 50000000000 |
| Binance Smart | binance-smart-chain | BNB | 56 | 15000000000 |
| Polygon | polygon | MATIC | 137 | 5000000000 |
+----------------+-------------+---------------+-----------+-------------+Prompt:
Show all bridges with their supported chains, sorted by 24-hour volume.Tool Called: list_bridges(include_chains=True)
Result:
+----+-------------+---------------+-----------------+----------------------------------+
| ID | Name | Display Name | Last 24h Volume | Chains |
+====+=============+===============+=================+==================================+
| 1 | polygon | Polygon | 1000000 | Ethereum, Polygon, Binance Smart |
| 2 | optimism | Optimism | 750000 | Ethereum, Optimism |
| 3 | arbitrum | Arbitrum | 500000 | Ethereum, Arbitrum |
+----+-------------+---------------+-----------------+----------------------------------+Prompt:
Get historical volumes for the Ethereum chain.Tool Called: get_historical_volumes(chain="ethereum")
Result:
+---------------------+---------------+---------------+---------------+---------------+
| Date | Deposit USD | Withdraw USD | Deposit Txs | Withdraw Txs |
+=====================+===============+===============+===============+===============+
| 2025-09-12 00:00:00 | 1000000.0 | 500000.0 | 150 | 100 |
| 2025-09-11 00:00:00 | 1200000.0 | 600000.0 | 180 | 120 |
| 2025-09-10 00:00:00 | 900000.0 | 450000.0 | 130 | 90 |
+---------------------+---------------+---------------+---------------+---------------+Prompt:
Show the 24-hour token stats for bridge ID 1 on Ethereum for September 12, 2025.Tool Called: get_day_stats(timestamp=1752499200, chain="ethereum", bridge_id=1)
Result:
+----------------+--------+----------+------------------+-------------------+------------------+-------------------+
| Token ID | Symbol | Decimals | Deposit Amount | Deposit USD Value | Withdraw Amount | Withdraw USD Value|
+================+========+==========+==================+===================+==================+===================+
| 0xa0b869... | USDC | 6 | 2000000 | 2000000.0 | 0 | 0.0 |
| 0xc02aaa... | ETH | 18 | 1000000000000000 | 1500000.0 | 500000000000000 | 750000.0 |
| 0xdac17f... | DAI | 18 | 0 | 0.0 | 1000000000000000 | 1000000.0 |
+----------------+--------+----------+------------------+-------------------+------------------+-------------------+Prompt:
Analyze the volume data for the Polygon bridge using historical volumes.Tool Called: get_historical_volumes(chain="polygon", bridge_id=1), followed by analyze_bridge_volume
Result:
Analyze the following volume data for the bridge 'Polygon':
+---------------------+---------------+---------------+---------------+---------------+
| Date | Deposit USD | Withdraw USD | Deposit Txs | Withdraw Txs |
+=====================+===============+===============+===============+===============+
| 2025-09-12 00:00:00 | 800000.0 | 400000.0 | 120 | 80 |
| 2025-09-11 00:00:00 | 900000.0 | 450000.0 | 140 | 90 |
| 2025-09-10 00:00:00 | 700000.0 | 350000.0 | 100 | 70 |
+---------------------+---------------+---------------+---------------+---------------+
Key insights:
- The Polygon bridge shows consistent deposit and withdrawal activity over the past three days.
- Deposits are roughly double the withdrawals in USD value, indicating higher inflow than outflow.
- Transaction counts are stable, with deposits averaging 120 transactions per day.This project is licensed under the MIT License. See the LICENSE file for details.
Fetch and return a 24hr token volume breakdown for a bridge on a specific day in a table format.
Parameters:
- timestamp: integer (required) - Unix timestamp for the day (data for 24hr period starting at 00:00 UTC).
- chain: string (required) - Chain slug (from list_chains).
- bridge_id: integer (optional) - The ID of the bridge (obtain from list_bridges).
Returns a table of token stats with columns: token id, symbol, decimals, deposit amount, deposit usd value, withdraw amount, withdraw value, sorted by deposit usd value in descending order.
| Name | Required | Description | Default |
|---|---|---|---|
| timestamp | Yes | ||
| chain | Yes | ||
| bridge_id | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It explains the timestamp semantics (24hr period starting at 00:00 UTC), return format, and sorting order. However, it does not disclose behavior for null bridge_id (whether it aggregates all bridges or errors), data availability, error handling, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the purpose, followed by parameter details and return format. It uses a structured list but could be more visually separated (e.g., bullet points). No unnecessary information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description explains the return format in detail (columns and sorting). It covers parameter semantics adequately. However, it lacks information on error conditions, pagination, or limits, which for a simple fetching tool is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds significant meaning beyond the schema. It explains timestamp as a Unix timestamp for the day, chain slug from list_chains, and bridge_id as optional from list_bridges. The timestamp semantics (24hr period starting 00:00 UTC) are explicitly defined, adding clarity beyond the schema's type-only definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: fetching a 24hr token volume breakdown for a bridge on a specific day. It uses the specific verb 'Fetch and return' and identifies the resource (bridge). However, it does not explicitly differentiate from siblings like 'get_historical_volumes', though the day-specific nature and token breakdown provide implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description mentions parameters that reference 'list_chains' and 'list_bridges', suggesting prerequisites, but does not state usage context or exclusions. Sibling tools exist (e.g., get_historical_volumes) with no comparison provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and return historical volumes for a bridge, chain, or specific bridge on a chain in a table format.
Parameters:
- chain: string (required) - Chain slug (from list_chains) or 'all' for all chains.
- bridge_id: integer (optional) - The ID of the bridge (obtain from list_bridges).
Returns a table of historical volumes with columns: date, depositUSD, withdrawUSD, depositTxs, withdrawTxs.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | Yes | ||
| bridge_id | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions the return format (table with columns), which adds basic behavioral context beyond the schema, but lacks details on data range, pagination, rate limits, or edge cases. Since no annotations exist, the description carries full burden but falls short of fully transparent disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: one main sentence stating purpose, followed by two bullet points detailing parameters. Every sentence provides necessary information without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers parameter semantics and output columns adequately. However, it could be improved by mentioning data range availability (e.g., all-time or limited period) and ordering of results. The output schema helps, but missing this context slightly reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter: chain specifies the source via list_chains and includes the special value 'all', and bridge_id is sourced from list_bridges. This adds substantial meaning beyond the schema's empty descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches historical volumes for a bridge, chain, or specific bridge on a chain, using specific verbs and resources. It distinguishes itself from sibling tools like get_day_stats (daily stats) and get_transactions (transaction details) by focusing on volume data and offering flexible filtering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when historical volume data is needed for a bridge or chain, but it does not explicitly state when to use this tool over siblings, nor does it provide exclusion criteria or alternatives. The context from sibling names is not leveraged in the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and return all transactions for a bridge within a specified date range in a table format.
Parameters:
- bridge_id: integer (required) - The ID of the bridge (obtain from list_bridges).
- start_timestamp: integer (optional) - Start Unix timestamp for the date range.
- end_timestamp: integer (optional) - End Unix timestamp for the date range.
- source_chain: string (optional) - Filter transactions bridging from this source chain.
- address: string (optional) - Filter transactions where this address is 'from' or 'to' (format: {chain}:{address}).
- limit: integer (optional) - Limit number of transactions returned (max 6000).
Returns a table of transaction data with key metrics.
| Name | Required | Description | Default |
|---|---|---|---|
| bridge_id | Yes | ||
| start_timestamp | No | ||
| end_timestamp | No | ||
| source_chain | No | ||
| address | No | ||
| limit | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions 'Fetch and return' assuming read-only, and specifies max limit of 6000. However, it does not disclose potential side effects, rate limits, authentication needs, or pagination behavior. Output description is vague ('key metrics').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with a clear purpose sentence followed by bullet points for parameters. Each sentence adds value and is not redundant. It is appropriately front-loaded but could be slightly more concise by removing the 'Returns a table' line as output schema exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters and no annotations, the description covers inputs adequately but leaves output vague ('key metrics'). Output schema exists, so return values are not required per rules, but operational details like pagination or error cases are missing. Completeness is average given context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description provides detailed explanations for each parameter, including types, requirements, and formats (e.g., address format {chain}:{address}, limit max 6000). This adds significant value beyond the raw schema, though some clarity on default behavior for optional params could be improved.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Fetch and return all transactions' with a specific resource (bridge) and scope (date range, table format). It explicitly distinguishes from siblings like get_day_stats and get_historical_volumes which are aggregated metrics, while this is raw transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool vs alternatives. It implies usage for fetching transaction data with filters, but lacks guidance on when not to use it (e.g., for summary statistics). The pointer to obtain bridge_id from list_bridges is helpful but not sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and return a list of all bridges from DeFiLlama in a table format, sorted by last24hVolume in descending order.
Parameters:
- include_chains: boolean (optional, default False) - Whether to include current previous day volume breakdown by chain.
Returns a table of bridges data with columns: id, name, displayName, last24hVolume, chains.
| Name | Required | Description | Default |
|---|---|---|---|
| include_chains | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses sorting order ('last24hVolume descending'), return format (table with columns), and the effect of the optional parameter (include chain breakdowns). This provides sufficient behavioral insight for a read-only list tool, though it could mention data freshness or potential limitations like pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a concise two-sentence block with a bullet-style parameter explanation. It front-loads the main action and sorting, then clearly details the optional parameter. Every sentence adds value without redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 optional parameter, output schema exists), the description covers the essential return columns and behavior. It adequately sets expectations for a list operation. However, it could mention whether data is real-time or includes a timestamp, and that it is a read-only operation (though implied). Overall, it is substantially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'include_chains' is explained in detail: 'Whether to include current previous day volume breakdown by chain.' The input schema only provides type info (boolean/null, default false), so the description adds critical semantic meaning about the parameter's effect. This fully compensates for the 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Fetch and return a list of all bridges from DeFiLlama in a table format, sorted by last24hVolume in descending order.' It clearly identifies the action, resource, and key behavior. The sibling tools (get_day_stats, get_historical_volumes, get_transactions, list_chains) are distinct in function, so this tool's purpose is well-differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining a list of bridges, but does not provide explicit guidance on when to use this tool versus alternatives like list_chains or get_day_stats. No 'when-not-to-use' or alternative suggestions are given, leaving the agent to infer context from the tool's name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and return a list of all chain slugs from DeFiLlama in a table format, sorted by TVL in descending order.
No parameters required.
Returns a table of chains data with columns: name, gecko_id, tokenSymbol, chainId, tvl.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries behavioral disclosure. It specifies the return format (table with columns) and ordering (TVL descending). It doesn't mention potential errors or latency, but for a read-only list, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the main action, then parameter info, then output details. No wasted words, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and an output schema, the description covers everything: what it returns, the format, and the sorting. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so the schema coverage is 100%. Following the baseline rule (0 params = baseline 4), the description adds no extra parameter semantics but isn't needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches a list of all chain slugs from DeFiLlama in table format, sorted by TVL. This distinguishes it from sibling tools like get_transactions or list_bridges.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'No parameters required,' guiding the agent that no input is needed. It doesn't discuss when to use vs alternatives, but the simplicity makes this sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Each tool has a clear distinct purpose: listing bridges/chains, daily token stats, historical aggregate volumes, and transaction details. No two tools overlap in functionality.
All tool names follow a consistent 'verb_noun' pattern in snake_case: 'get_' for data retrieval and 'list_' for enumeration. No mixing of styles or vague verbs.
5 tools is well-scoped for the domain of bridge metrics. It covers discovery (list_bridges, list_chains) and detailed queries (day stats, historical volumes, transactions) without being overwhelming or sparse.
The tool set provides comprehensive coverage for a read-only bridge metrics API: listing all bridges and chains, retrieving daily token breakdowns, historical aggregate volumes, and individual transactions with filters. No obvious gaps for typical use cases.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Token swaps and honeypot/rug checks for AI agents on 8 chains, paid per-call in USDC via x402.
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