Network Management Working Group Y. Yang
Internet-Draft Q. Wu
Intended status: Informational Huawei
Expires: 22 April 2026 D. Lopez
Telefonica
N. R. Moreno
Deutsche Telekom
L. Tailhardat
Orange Research
G. Zeng
Huawei
19 October 2025
Applicability of MCP for the Network Management
draft-yang-nmrg-mcp-nm-01
Abstract
The application of MCP in the network management field is meant to
refactor network management operation and network capabilities as
tools and provide more agile and extensible architecture to expose
these AI integration capabilities. This document discusses the
applicability of MCP to the network management plane in the IP
network that utilizes IETF technologies.It explores MCP for network
exposure, multiple MCP server discovery generic workflow and
deployment scenarios.
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This Internet-Draft will expire on 22 April 2026.
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Table of Contents
1. Introduction
2. Terminology & Notation Conventions
2.1. MCP
2.2. Others
3. The values of coupling MCP with the network management
4. The high level Challenges in adopting MCP in NM
5. MCP for Network Exposure
5.1. The Third Party as IETF network Exposure Consumer
5.2. The Network Controller Consumes external sources
6. MCP Server Discovery
6.1. MCP core function
6.2. Procedure for Multi-MCP servers Discovery
7. Deployment Consideration in adopting MCP in the Network
Management
7.1. MCP Communication using Inter Processing Communication
7.2. The OSS and the Network Controller Communication using MCP
7.3. The Network Controller and the Network Device Communication
using MCP
7.4. The Network Gateway and the Network Device Communication
using MCP
8. MCP architecture Design for Network Management
8.1. Encapsulating Device Operations into MCP Tools
8.2. LLM for Intent-to-Tool-Request Translation
8.3. Closed-Loop Automation Execution Workflow
9. Interworking with the Network Management protocol and YANG data
models
10. MCP Usage Examples
10.1. Device Configuration using MCP+CLI
11. IANA Considerations
12. Security Considerations
13. Normative References
Authors' Addresses
1. Introduction
The Model Context Protocol (MCP) decouples LLMs from tools and
provides a standardized way for LLMs to access and utilize
information from different data sources and tools, making it easier
to build AI applications that can interact with external LLM models
and software tools and enable workflows automation.
MCP has seen rapid adoption across both startups and enterprises
since it announced in November 2024. Key use cases include AI coding
assistants in IDEs, data analysis tools that can query databases, and
productivity tools that can interact with services like Slack or
Google Drive.
The application of MCP for the network management is meant to
refactor network management operation and network capabilities as
tools and provide more agile and extensible architecture to expose or
consume these AI integration capabilities.
With integration of MCP into the network management system, it allow
you develop various rich AI driven network applications, realize
intent based networks management, automate workflows in the multi-
vendor heterogeneous network platform. By establishing standard
interfaces for tool encapsulation, intent translation, and closed-
loop execution within the network management system, MCP enables the
network management system to have:
* Unified operation abstraction through normalized MCP tool
definitions
* Seamless LLM integration via the structured protocol
* Automation Execution Ability
This document discusses the applicability of MCP to the network
management plane in the IP network that utilizes IETF technologies.
It explores MCP for network exposure, multiple MCP server discovery
generic workflow and deployment scenarios.
2. Terminology & Notation Conventions
The following terms are used throughout this document:
2.1. MCP
* *MCP Protocol*: MCP is an open standard designed to facilitate
communication between LLMs and external data sources or tools.
* *MCP Host*: The entity initiating the LLM request.
* *MCP Client*: A built-in module within a host, specifically
designed for interaction with the MCP server.
* *MCP Server*: A dedicated server that interacts with MCP clients
and provides tools.
* *CLI*: Command Line Interface
2.2. Others
* *LLM*: Large Language Model
* *NETCONF*: Network Configuration Protocol [RFC6241]
* *RESTCONF*: RESTful Network Configuration Protocol [RFC8040]
* *SNMP*: A Simple Network Management Protocol [RFC2576]
3. The values of coupling MCP with the network management
+---------------+ +---------------+
| | | |
| 3rd Party | | 3rd-party
| AI Agent | | Tools/Contents|
+-----/---\-----+ +---------------+
| | | |
| | ----------------- \ /
/////// \\\\\\\
|| ||
|| ||
| MCP Eco-system |
|| ||
\\\\\\\ ///////
/ \ ----------------- | |
| | | |
+---------------+ +----- \---/----+
| | | |
| Network MCP | | In-Network |
| Server | | Service |
(network exposure) (e.g.,Digital assistant)
+---------------+ +---------------+
/ \ / \
| | | |
+------+---+-------------------+---+----+
| |
| Network Intelligence |
| |
| Agentic + MCP Architecture Paradigm |
| |
+---------------------------------------+
There are 3 values for MCP coupling with the network management -
Network MCP Server support * Exposing network capabilities as MCP
Servers for 3rd-party AI Agents & applications
* In Network Service
- Empowering network services by leveraging MCP ecosystem tools &
contents
- Network service as a unified interface to various and rich
capabilities for network users
* Network Management Intelligence
- Making network architecture really agile and friendly for
innovation
- Decoupling network management functions into network agents and
network tools
4. The high level Challenges in adopting MCP in NM
* Protocol Design
- Error Handling o Although MCP provides basic error codes, MCP
does not yet enforce a entire error-handling mechanism, and its
scope is currently limited to discovery and invocation,
omitting crucial aspects like tool governance, versioning, or
lifecycle management.
- Stateful o The protocol's reliance on stateful Server-Sent
Events (SSE) can create significant complexities when
integrating with inherently stateless REST APIs, requiring
developers to manage state externally. This can be
particularly challenging for remote MCP servers due to network
latency and instability, complicating load balancing and
horizontal scaling efforts.
- Context Handling o There are also concerns that multiple active
MCP connections could consume significant tokens in the LLM's
context window. This can directly impact an LLM's performance,
slowing down responses and potentially hindering its ability to
maintain focus and reason effectively over extended or complex
interactions.
* Security Consideration
- Malicious Actors The protocol's ability to grant LLMs access to
external systems introduces potential vulnerabilities that
require careful consideration o Prompt injection, where
malicious instructions embedded in user inputs or tool
descriptions could lead to unintended actions by the LLM o Tool
poisoning, where attackers modify tool definitions, or rug
pulls (similar to tool poisoning but occurs post-installation)
o Tool shadowing, where a malicious server creates a tool with
the same name as a legitimate tool from another server to
intercept calls
- Security enforcement o MCP itself lacks inherent security
enforcement mechanisms, relying heavily on external
implementations for authentication and authorization, which
were not initially well-defined within the protocol.
- Identity Management o Determining clear identity management -
whether requests originate from the end user, the AI agent, or
a shared system account - remains an area needing clearer
definition.
5. MCP for Network Exposure
Network exposure is the process of making network capabilities, such
as data and connectivity services, available to external users,
applications, and developers through secure APIs. It allows for more
agility and the creation of programmable networks. The MCP can be
used to expose network capabilities to AI applications or consume
external sources for LLMs.
5.1. The Third Party as IETF network Exposure Consumer
3rd Party
+------------------+
| Consumer |
| +------------+ |
| | | | 4. Authoriz and Consume
| | MCP Client <-+------------------------+
+---+-+-------^--+-+ |
2.Discover |3. List of |
and Authz | Available APIs |
| | |
| | |
+---+-V-------+--+------------+ +---V--------+
| | MCP Server | | |Tools |
| +------------+ |1.Publish|+----------+|
| <---------+|Simulation||
| Network Exposure Agent | || API ||
| /Network Controller |4. Authz |+----------+|
| +---+ +---+ +---+ <---------> |
| |NF1| |NF2| |NF3| ... | |+----------+|
| +---+ +---+ +---+ | Heart ||Other APIs||
| <--------->+----------+|
+-----------------------------+ Beat +------------+
Step 1: External tools or data source publish a set of APIs to MCP
server in the Network Controller. Step 2: MCP client send specific
tools request to discover tools and MCP Server provide authorization
to the MCP client. Step 3: After sucessful authorization, MCP server
return API list corresponding to tools request sent by the MCP
client. Step 4: MCP Client invokes tools with authorization.
5.2. The Network Controller Consumes external sources
+---------------+
| Data Source |
| +-----------+ |
| | MCP Server| |
+-+-----^-----+-+
|2. Consume external sources
|
+------+-----V-----+-----------+
| | MCP Client|0.Preconfig MCP
+--------------+ | +-----------+ Server Address
| IETF |1.MCP Service Request |
| Network +--------> |
| Management |3.MCP Service Response |
| AI Agents <--------+ |
+--------------+ | |
| Network Controller |
| |
+------------------------------+
Step 0: MCP Client is preconfigured with the MCP Server address.
Step 1: IETF Network Management AI Agent sends a MCP Service Request
to the MCP client within the Network Controller. Step 2: The MCP
client discover tools provided by the external MCP server. Step 3:
The MCP client provide available tools list to the IETF Network
Management AI Agent.
6. MCP Server Discovery
The MCP Server Discovery involves clients querying servers to find
available tools, resources, and functions. In case of MCP servers
are distributed in different locations, MCP Respository can be
established to keep track of the location of each MCP servers.
6.1. MCP core function
+------------+ 2.Discovery ---------------+
| Agents +-----------+ MCP |
|(MCP Client)+-----------+ Respository |
+-+----------+ 3. Authz +--------^-------+
|4. Consume |1.Registration
| +-------------+---------------+-------+-
+----------V-+ +-----+-------+ +------+------+
|MCP Server 1| |MCP Server 2 | | MCP Server 3|
+------------+ +-------------+ +-------------+
------- ----- -----
///FM PM \\\ /// \\\ /// \\\
| | || Memory | || |
| Routing ACL| | | | Templates|
\\\Policy /// || Database | || |
------- \\\ /// \\\ ///
----- -----
• MCP Repository: * Maintain the description of MCP servers * Support
MCP server discovery for Client.
• MCP client: consuming the services provided by MCP servers
• MCP servers: including authentication/session/policy tools, the
memory/prompts used for Agents
6.2. Procedure for Multi-MCP servers Discovery
+------------------+ +----------+ +-------+ +------+
|Network Management| | | | | | |
| AI Agent | | MCP | | MCP | |Tools |
| (MCP Client) | |Repository| |Servers| | |
+---------+--------+ +----+-----+ +---+---+ +---+--+
| | | 0. Sync the info of tools
| | |<------------+
| |1. Registration |
| |<------------+ |
| | | |
| +-------------+----------+ | |
| | Repository | | |
| |MCP Server1:ID 1, Capability, Tools |
| | | | |
| |MCP Server2:ID 2, Capability, Tools |
| +------------- ----------+ | |
| 2.1 Discovery | | |
+------------------> | |
| +------+------+ | |
| | Search for | | |
| | Proper MCP | | |
| | Server | | |
+-------------+ | |
| 2.2 Address of MCP Server | |
<------------------+ | |
3. oAuth Authz | |
<------------------------------->| |
| 4. Consume Tools/Resources/Prompts |
+------------------+-------------|-------------|
| | |
Step 0: The MCP Server syncs up on the info of tools, upon tools is
added or removed, tools changes will be automatically syned up with
the MCP server. Step 1: Each new MCP server will register to the
centralized MCP registry. Step 2.1: MCP Client send the MCP service
request to the MCP registry for specific capability. Step 2.2: The
MCP registry return specific MCP server to the MCP client. Step 3:
The MCP Client request authorization from the MCP server. Step 4:
The MCP Client invoke specific tools with authorization.
7. Deployment Consideration in adopting MCP in the Network Management
This section describes MCP deployment requirements for network
management environments, followed by implementation scenarios. Key
architectural requirements include:
* Function-Specific MCP Servers: To maintain proper architecture and
performance with growing tool volumes, servers should be
categorized by network management function. Typical categories
include network log analysis, device configuration management,
energy consumption management, and security operations.
* Secure and Scalable Architecture: The architecture must:
- Enforce strict access controls limiting MCP operations to
authorized AI models and users
- Scale efficiently with increasing network device counts while
maintaining performance
* Automated Workflows: MCP implementations should support LLM-
coordinated automation of:
- Real-time monitoring and diagnostics
- Fault remediation workflows
- Other common management operations to reduce operator workload
While these core requirements apply universally, operational
characteristics vary based on deployment location (on-premises vs.
remote). The following subsections detail these deployment
scenarios.
7.1. MCP Communication using Inter Processing Communication
In this network scenario, both the MCP client and the MCP server are
deployed within the same network controller. The MCP client
communicate with the MCP server using inter processing communication.
In the meanwhile, the LLM model as pre-trained model should also be
deployed in the same Network controller.
+----------------------------+
| |
| OSS/BSS |
| |
+----------------------------+
+--------------------------+
|Network Controller (Network AI Agent)
| |
| +------+Natrual +----+ |
| |MCP |Language|LLM | |
| |Client|------- | | |
| +---+--+Command +----+ |
| | |
| +---+--+ |
| |MCP | |
| |Server| |
| +------+ |
+------------+-------------+
|NETCONF/Telemetry/CLI
|-----------------+--+------------+
+---+-----+ +----+----+ +----+----+
| Network | | Network | |Network |
| Device | | Device | |Device |
+---------+ +---------+ +---------+
7.2. The OSS and the Network Controller Communication using MCP
In this network scenario, the MCP client is deployed in the OSS/BSS
while the MCP server is deployed in the Network Controller, the MCP
client and the MCP server communicated using SSE. In the meanwhile,
the LLM model can be pre-trained LLM model collocated with the MCP
client or the LLM model in the Cloud.
+--------------------------+
| |
| OSS/BSS |
| |
| +------+Natrual +----+- |
| |MCP |Language|LLM | |
| |Client|------- | | |
| +---+--+Command +----+ |
+------+-------------------+
|
|
+------+-------------------+
|Network Controller (Network AI Agent)
| |
| | |
| +---+--+ |
| |MCP | |
| |Server| |
| +------+ |
+------------+-------------+
|NETCONF/Telemetry/CLI
|-----------------+--+------------+
+---+-----+ +----+----+ +----+----+
| Network | | Network | |Network |
| Device | | Device | |Device |
+---------+ +---------+ +---------+
7.3. The Network Controller and the Network Device Communication using
MCP
In this network scenario, The MCP client is deployed in the network
controller while the MCP server is deployed in the network devices.
The MCP client communicates with the MCP server using the MCP
protocol. LLM model is pre-trained model and deployed in the same
Network Controller as the MCP client.
Network devices usually have limited resources (CPU, memory, etc.).
Deploying MCP Server may occupy a large amount of resources,
affecting the normal operation of the device.
+--------------------------+
|Network Controller (Network AI Agent)
| |
| |
| +------+Natrual +----+ |
| |MCP |Language|LLM | |
| |Client|------- | | |
| +---+--+Command +----+ |
+------+-------------------+
|NETCONF/CLI
+--------------+--+---------------+
| | |
+---+-----+ +----+----+ +----+----+
| MCP | | MCP | | MCP |
| Server1 | | Server2 | |Server3 |
+---------+ +---------+ +---------+
Network Device Network Device Network Device
7.4. The Network Gateway and the Network Device Communication using MCP
In this network scenario, The MCP client is deployed in the network
gateway device while the MCP server is deployed in each network
devices. The MCP client communicates with the MCP server using the
MCP protocol. LLM model is pre-trained model and deployed in the
same Network gateway as the MCP client.
Network devices usually have limited resources (CPU, memory, etc.).
Deploying MCP Server may occupy a large amount of resources,
affecting the normal operation of the device.
+--------------------------+
|Network Gateway (Network AI Agent)
| |
| |
| +------+Natrual +----+ |
| |MCP |Language|LLM | |
| |Client|------- | | |
| +---+--+Command +----+ |
+------+-------------+
|NETCONF/CLI
+-----------------+---------------+
| | |
+---+-----+ +----+----+ +----+----+
| MCP | | MCP | | MCP |
| Server1 | | Server2 | |Server3 |
+---------+ +---------+ +---------+
Network Device Network Device Network Device
8. MCP architecture Design for Network Management
┌──────┐
│ User │
└───┬──┘ Step b.LLM for Intent to tools
1 │ 9 request translation
┌──────────│─────────────────┐ (1,3,4,9)
│ ┌────────┴───┐3,8 ┌───┐ │
│2│ MCP Client ├───────┤LLM│ │
│ └────────┬───┘4,7 └───┘ │ Step c.Close Loop Execution workflow
│ │ │ (5,6,7,8,)
│ 5│6 │
│ │ │
└──────────│─────────────────┘
│ Step a.Encapsulating network
┌──────────┴───┬─────────────┐ operations into MCP tools
┌────┴─────┐ ┌─────┴─────┐ ┌─────┴────┐
│MCP Server│ │ MCP Server│ │MCP Server|
└──────────┘ └───────────┘ └──────────┘
8.1. Encapsulating Device Operations into MCP Tools
* Objective: Standardize device operations into modular, reusable
tools.
* Implementation:
- Tool Abstraction: Vendor-specific commands are wrapped into
discrete MCP Tools with uniform schemas.
- Tool Registry: A centralized database stores MCP Tools with
metadata (e.g., names, descriptions, parameters).
* Benefits:
- Eliminates manual translation of commands across different
vendors
- Enabling the plug-and-play integration of new device types.
8.2. LLM for Intent-to-Tool-Request Translation
* Objective: Allow AI models (such as Claude) to understand natural
language commands and trigger operations.
* Workflow:
- Intent Recognition: The LLM first analyzes the user's natural
language query to identify：
o The user's intent or goal
o Required actions or operations
o Entities, parameters, and constraints mentioned
o Context from previous interactions
- Tool Discovery and Toolchain Generation: The LLM access tool
descriptions provided by MCP servers, and matches the
identified intent with available tools.
- Parameter Extraction and Mapping: The LLM maps natural language
references to structured parameter names and extracts relevant
information from the user query.
- Structured Invocation Generation: The LLM generates properly
formatted tool calls following MCP's protocol.
* Benefits:
- Bridge natural language to tool invocation requests in a fixed
format, then return this request to the client, enabling the
client to properly parse the request.
8.3. Closed-Loop Automation Execution Workflow
* Objective: Realize the closed loop of "voice/text commands →
automatic execution".
* A general workflow is as follows:
- User Input Submission: An operator submits a natural language
request to the MCP client. And The MCP client forwards this
request to the LLM.
- LLM Intent Processing: The LLM parses the input, identifies the
operational intent, and forwards a structured request to the
MCP client, which queries the MCP Server to retrieve the
available tools. The information would include the functional
description, required parameters of tools.
- LLM Toolchain Decision:
o The LLM evaluates the context and if tools are required,
select and sequence tools.
o The decision is sent back to the MCP Client and then MCP
Client will execute tools via server.
- Tool Execution: The MCP Server executes the translated commands
on target devices and returns results to the client.
- Result Aggregation & Feedback: The MCP Client collates tool
outputs (success/failure logs) and forwards them to the LLM for
summarization.
* Benefits:
- Tools safely retry/rollback.
- Full traceability of LLM decisions and tool executions.
9. Interworking with the Network Management protocol and YANG data
models
MCP can be seen as AI protocol and used to invoke AI integrated
capabilities. MCP is not in the position to replace the network
management and YANG data model. Instead, it can be integrated
together, e.g., * Integrated MCP with CLI, allow the MCP client
invoke CLI capabilities; * Integrated MCP with YANG, allow the MCP
client invoke YANG interface related capabilities;
10. MCP Usage Examples
10.1. Device Configuration using MCP+CLI
In this example, MCP server is implemented by Server and expose all
CLI interfaces and documentation as tools to the MCP Client. The
Nework controller implement the client to interact with MCP server in
the Network device.
The MCP server provides the following registered tool descriptor
information:
Tools description: It describes the name, use, and parameters of
tools.
Tools implementation: MCP implementation describes how the tools are
invoked.
See Tool descriptor information example as follows:
# Tool Descriptor
[
{
"name": "batch_configure_devices",
"description": "Batch Configure Network Devices"，
"parameters": {
"type": "object",
"properties": {
"device_ips": {"type": "array", "items": {"type": "string"}, "description": "Device IP List"}，
"commands": {"type": "array", "items": {"type": "string"}, "description": "CLI Sequence"}，
"credential_id": {"type": "string", "description": "Credential ID"}
}，
"required": ["device_ips", "commands"]
}
},
{
"name": "check_device_status",
"description": "Check the Status of Network Devices"，
"parameters": {
"type": "object",
"properties": {
"device_ip": {"type": "string"},
"metrics": {"type": "array", "items": {"enum": ["cpu", "memory", "interface"]}}
}
}
}
]
# Tool Implementation
from netmiko import ConnectHandler
from mcp_server import McpServer
app = FastAPI()
server = McpServer(app)
#Connection Pool Management
devices = {
"192.168.1.1": {"device_type": "VendorA-XYZ"，"credential": "admin:XYZ@password"},
"192.168.1.2": {"device_type": "VendorB-ABC","credential":"admin:ABC@passowrd"}
....
}
@server.tool("batch_configure_devices")
async def batch_config(device_ips: list,commands: list,credential_id: str):
results = {}
for ip in device_ips:
conn = ConnectHandler(
ip = ip,
username = devices[ip]["credential"].split(':')[0],
password = devices[ip]["credential"].split(':')[1],
device_type = devices[ip]["device_type"]
)
output = conn.send_config_set(commands)
results[ip] = output
return {"success": True, "details": results)
@server.tool("check_device_status")
async def check_status(device_ip: str, metrics: list):
status = {}
if "cpu" in metrics:
status["cpu"] = get_cpu_usage (device_ip)
if "memory" in metrics:
status["memory"] = get_memory_usage(device_ip)
return status
Suppose a user submits a request (via the client) such as "Configure
OSPF Area 0 with process ID 100 for all core switches in the Beijing
data center," the MCP client retrieves the necessary tooling
descriptor information from the MCP server and forwards it along with
the request to the LLM. The LLM determines the appropriate tools and
responds in JSON format as follows:
{
"method": "batch_configure_devices",
"params": {
"device_ips":["192.168.10.1",....,"192.168.10.10"],
"command": [
"router ospf 100",
"network 192.168.0.0 0.0.255.255 area 0"
]
}
}
}
The MCP server responds to the call instruction, converts it into the
below CLIs of different vendors, and then the devices execute the
CLIs. The results are returned to the MCP client in Json as below
and are forwarded to the LLM. The LLM parses the response, generates
a natural-language summary, and sends it back to the client for final
presentation to the user.
# Convert to CLI commands of different vendors
"commands": [
"system-view",
"ospf {{process_id}}",
"area {{area_id}}",
"network {{network_address}} {{wildcard_mask}}"
]
"commands": [
"configure terminal",
"router ospf {{process_id}}",
"network {{network_address}} {{wildcard_mask}} area {{area_id}}",
"end",
"write memory"
]
#Feedbacks received by the MCP client of different vendors
{
"status": "success",
"message": "OSPF configuration applied successfully on device 192.168.10.1",
"commands_executed": [
"system-view",
"ospf 100",
"area 0.0.0.0",
"network 192.168.10.0 0.0.0.255"
]
}
{
"status": "success",
"message": "OSPF configuration applied successfully on device 192.168.10.1",
"commands_executed": [
"configure terminal",
"router ospf 100",
"network 192.168.10.0 0.0.0.255 area 0",
"end",
"write memory"
]
}
# Natural lanauge summary of success or failure:
{
"192.168.10.1": "Configure Successfully, take 2.3 seconds",
"192.168.10.2": "Error: no response from the device",
}
11. IANA Considerations
This document has no IANA actions.
12. Security Considerations
The MCP protocol needs to consider scenarios where either the client
or server encounters issues, such as crashes. If one or both parties
go offline during communication, the entire process may remain stuck
waiting for messages, potentially leading to an infinite loop.
Furthermore, certain tool operations may be interrupted, and some
irreversible network management operations could be affected.
Due to network latency, some operations might not return in time, yet
from the user's perspective, these operations may appear either
unexecuted or failed. If the user then initiates another tool
request to the server, problems may occur.
For complex network management workflows, while LLM's tool invocation
process may generally function correctly, issues can arise in the
details. Users must verify each LLM operation to prevent unintended
hazardous actions.
13. Normative References
[RFC2576] Frye, R., Levi, D., Routhier, S., and B. Wijnen,
"Coexistence between Version 1, Version 2, and Version 3
of the Internet-standard Network Management Framework",
RFC 2576, DOI 10.17487/RFC2576, March 2000,
<https://www.rfc-editor.org/rfc/rfc2576>.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
<https://www.rfc-editor.org/rfc/rfc6241>.
[RFC8040] Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,
<https://www.rfc-editor.org/rfc/rfc8040>.
Authors' Addresses
Yuanyuan Yang
Huawei
China
Email: yangyuanyuan55@huawei.com
Qin Wu
Huawei
China
Email: bill.wu@huawei.com
Diego Lopez
Telefonica
Spain
Email: diego.r.lopez@telefonica.com
Nathalie Romo Moreno
Deutsche Telekom
Germany
Email: nathalie.romo-moreno@telekom.de
Lionel Tailhardat
Orange Research
France
Email: lionel.tailhardat@orange.com
Guanming Zeng
Huawei
China
Email: zengguanming@huawei.com